botswana hiv aids case study geography

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Case studies illustrate the causes of health issues. They explain their growth, effects on the population and the strategies involved in managing development and health in the 21st century.

Case study of a global disease

Aids- location.

AIDS (Acquired Immunodeficiency Syndrome) is caused by HIV which, over time, wears down the immune system . This lack of natural resistance makes an infected person extremely susceptible to picking up viruses which, in most cases, eventually leads to death.

Every country in the world has, or has had, someone living with AIDS. However, the distribution of cases around the world is very uneven, with over 70 per cent in Africa . Even then the vast majority of the cases found in Africa are located south of the equator with most of these in South Africa itself.

Look at the map above.

Describe, in detail, the global distribution of AIDS.

HIV/AIDS is usually passed on through contact with the blood or body fluids of an infected person. The main ways people contract HIV/AIDS are:

Effects of AIDS

In a developed country AIDS is often found within specific groups such as intravenous drug users . News of someone contracting the virus can have a detrimental emotional impact on relatives and families, as well as on the individual.

There is a great cost involved in treating the disease, eg with antiretroviral drugs , and in research costs.

In a developing country the cost of medicine to control the disease means that most people go without treatment. AIDS is a debilitating disease which means that eventually those infected will not be able to work, lowering the productivity and potential wealth of a country.

Development may be hindered which leads to fewer jobs and less wealth in a country. The death rate will increase and life expectancy decreases.

In countries like South Africa or Uganda where AIDS is endemic, children may be left without parents and brought up by their grandparents. Entire middle-aged populations may be missing from societies. There may also be a loss of tourist revenue if it becomes known that there are specific problems with disease in the area.

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botswana hiv aids case study geography

The gleaming floors, white-frocked technicians and humming electronic equipment of the Botswana-Harvard HIV Reference Laboratory here in Botswana's capital are distant in more ways than geography from the dusty villages and crowded mining compounds on the frontline of Botswana's desperate struggle against HIV/AIDS. But closing the gap between the resources available at this modern new facility, and the nearly 40 per cent of the adult population infected with the deadly virus, is at the heart of Botswana's high-stakes effort to provide comprehensive HIV/AIDS treatment to all of its citizens. In January, Botswana became the first country in Africa to offer expensive, but life-saving, anti-retroviral drugs (ARVs) and other medications to all who need them through the public health system.

It is a costly and ambitious undertaking, one that many health care experts say cannot be done in Africa. But for the 330,000 Botswanan adults estimated to be HIV-positive, access to ARVs and to ongoing care, counselling and testing, is a matter of life or death. The vast but sparsely-populated territory has the highest HIV infection rate in the world (see table, below). Some 26,000 people in this country of less than 1.6 million died from AIDS-related illnesses last year alone. "We are threatened with extinction," President Festus Mogae told the UN General Assembly last year. "People are dying in chillingly high numbers. It is a crisis of the first magnitude."

More than Botswanan lives may be at stake, however. For years, some international health experts, backed by many donor governments and agencies and the powerful pharmaceutical industry, have argued that poverty and the absence of infrastructure make it impossible to successfully treat large numbers of HIV-positive people in developing countries with AIDS medications. Rather than waste resources on a failed effort to treat those already ill, they assert, scarce funds should be spent preventing new infections through education and prevention programmes.

Activists counter that pilot projects have demonstrated the feasibility of treatment programmes in developing countries, and that only a combination of treatment and prevention can turn the tide against the disease. Many advocates charge that opposition to large-scale treatment programmes is fueled more by concerns for patent rights and profits than genuine doubts about practicability.

 Botswana's AIDS epidemic, 2001


 1.6 million

 Adult population (15-49)

 Total adults with HIV

 Adult infection rate

 Adult women with HIV

 Adult men with HIV

 Children with HIV (0-14)

 Older adults with HIV (50+)

 Total deaths (2001)

 AIDS orphans (0-14)

 Life expectancy (1987)

 Projected life expectancy (2005)

 Source: UN Africa Recovery from UNAIDS, World Bank data

Botswana is the first African test case. Success in treating large numbers of patients will buttress the argument for greatly expanded treatment efforts in the rest of Africa and other developing regions. Failure will badly undermine the call for greater treatment access for the world's poor. Although the Joint UN Programme on HIV/AIDS (UNAIDS) has long maintained that both prevention and treatment are necessary in the campaign against AIDS, fewer than 30,000 of the almost 29 million Africans infected with the virus have access to the ARV drugs that have dramatically reduced death rates in rich countries (see " A grim prognosis for AIDS in Africa" ).

Slow but steady progress

If any country in sub-Saharan Africa can implement a comprehensive HIV/AIDS prevention care and treatment programme, observers say, it is Botswana. Unlike many of its neighbours, the country has enjoyed an unbroken period of peace and comparative prosperity since independence in 1966. Its government is widely regarded as among the most efficient and capable on the continent, and its annual per capita income of $3,300 is among the highest.

Still, the obstacles are formidable. Many Botswanans are migrant workers, employed in neighbouring South Africa for much of the year, but maintaining farms and families back home. Migrants are at particular risk of infection because of the increased likelihood of contact with prostitutes and other casual sex partners while away from home. Often unaware that they have become HIV-positive, and unwilling to seek out testing and counselling because of the stigma associated with the disease, migrants are thought to be an important factor in the spread of the virus.

For those who do seek medical help, there is the problem of locating it. For HIV patients outside the private sector, there are only two government referral hospitals, one in Gaborone and another in the north, in Francistown. There are two smaller, district hospitals in the country, but most public health care is delivered through local clinics offering only basic services.

The National AIDS Coordinating Agency (NACA) formally embarked on the national treatment programme in January this year. Dr. Banu Khan, NACA's national AIDS coordinator, told Africa Recovery that the government set a target of 19,000 people for enrolment in their first year of ARV treatment under a $27.5 mn programme in which people who require the drugs will get them for life. The ministry of health has calculated the cost of medications, testing and counselling at about $600 per person, per year. Over the first five years of the programme, the Gates Foundation will provide $50 mn to help Botswana strengthen its primary health care system, while the giant US drug manufacturer Merck will match that contribution with anti-retroviral medicines. The other half of the cost, some $100 mn, will be met by the government.

Success in treating large numbers of patients will buttress the argument for greatly expanded treatment efforts in the rest of Africa and other developing regions.

"As of June this year, we had an estimated 1,000 people enrolled," Dr. Khan noted. "We have 500 undergoing the treatment, while the remainder are still being screened to ascertain their precise treatment requirements." She termed that number "disappointingly" low, but said that more people are steadily coming forward. NACA says the volunteer patients include a "good mix" of educated and poorer rural people, some from the remote regions of the arid Kalahari in the west and northwest of the country.

Significantly, NACA officials say, initial indications are that very few patients have difficulty adhering to the complex ARV drug treatment regimes. The ability of poor and poorly educated patients to stick to strict medication schedules over a lifetime has been a major concern of health specialists and is an important aspect of Botswana's treatment initiative. Like Alcoholics Anonymous, NACA operates a "buddy system" whereby each patient is encouraged to form a special bond with someone close, who makes sure they remain on their medication schedule. The patients, in turn, counsel others who feel they may need help, to come forward.

Targeting mothers

Enrolling women in the programme is a key priority because they make up more than half of all infected adults. Dr. Khan said that NACA is especially concerned at the low intake of mothers in a programme intended to cut mother-to-child transmission of the HIV virus and keep infected mothers alive. Since the pilot project began, she said, only 2,000 women are currently undergoing treatment for AIDS-related illnesses. "We only opened up pilot sites two years ago. The percentage of mothers enrolled, however, is not desirable. It is low and must be increased. We have problems here, especially the one of stigma." Health officials said enrolment by pregnant mothers had only been in the 11-20 per cent range.

"Another problem is the status of women in relation to men," Dr. Khan added. Many women lack the power to control decisions about sexuality and remain under the authority of husbands, parents and in-laws all their lives. "How do you test someone if they do not get permission?", Dr. Khan asked.

"Then, with those who do enrol, they go home to a remote village with formula milk for their baby and are branded as suspect because they are not breast-feeding.... Mothers also worry about who will look after their baby if they die. But ARV therapy is now available in Botswana for these mothers and their babies, and I am hoping [enrolment] will increase now."

The country currently has 16 voluntary counselling and testing centres specifically for mothers, one in every district. These are stand-alone centres where one can discuss medical problems in privacy. "For example, in the latter part of last year, we had a conference for people living with HIV/AIDS and it drew 500 sufferers," Dr. Khan noted. "They went back to their homes and formed support groups to reduce stigma."

Botswana is supporting the new drug treatment policy with an expanded and more aggressive education campaign, modeled in part after Uganda.

Dr. Khan said that NACA urgently needs more trained staff. "We have found that if you have a trained nurse dealing with many people in a rural clinic, for example, she does not have the time to counsel every HIV patient. So we are building a system of lay counselors, like social workers. For this, we do not necessarily need nurses and we have a programme to employ 500 such lay counselors. We are hoping they will also play a key role in reducing stigma."

She said that people living with AIDS, both from the educated urban classes and rural communities, are increasingly aware that the government is providing free lifelong treatment. "These people are with us on a voluntary basis. No one is coerced. We counsel them on positive living, about prevention, about the importance of remaining on the treatment even if they feel better. And they usually go home and spread this positive message."

Staff shortages severe

At present, NACA employs 10 doctors working full time on HIV/AIDS at the Princess Marina Hospital in Gaborone, and five at each of the other hospitals. Patients are also seen at the smaller health facilities, some of them mobile clinics, around the country. Uniquely for an African country, NACA says, almost no one is more than 8 km away from a clinic where they can seek medical help. Even in the remotest areas of the Kalahari, most people are just 15 km away. These clinics decide what sort of treatment people need, and either refer them to a hospital or provide them with ambulance transport if required.

Ms. Catherine Sozi, a British-trained Ugandan doctor based at the UNAIDS office in Pretoria, South Africa, said Botswana can sustain its national health scheme for AIDS patients even though the drugs are required for life. "However, there is an acute, absolute shortage of doctors, nurses and counselors in Botswana's health care system," she said, citing a recent UNAIDS assessment. "Although we did not have time to calculate the number of extra health workers needed for the ARV programme, the numbers are substantial. If a first recruitment for ARV treatment would cost one hour of a doctor's time, recruiting 10,000 new patients in three months, for example, would require at least 20 fulltime doctors doing nothing else but supervising these patients."

The shortage of doctors, pharmacists, nurses and counselors is compounded by the fact that over 90 per cent of doctors in Botswana are foreigners who do not speak Setswana. Counselors too are recruited from abroad and need to spend time becoming familiar with the local culture. Many spend only a brief period in the country, thus exacerbating the need for frequent training and supervision to ensure proper medical care. There also is concern that many nurses, once trained and registered, emigrate to better-paid jobs abroad.

The government is seeking to recruit up to 200 new doctors from South Africa, Cuba and other nations to administer the drug programme. "In return for their travel and accommodation expenses, many are coming to give their time free of charge," Dr. Khan explained. "They know the government is serious in addressing this epidemic."

The shortage of pharmacists outside the major hospitals is another problem. UNAIDS found that Botswana's few pharmacy technicians already have to manage drug supplies and distribution in the hospital and surrounding clinics. "They need support if they are to handle sensitive drugs like ARVs," Dr. Sozi said. Because Botswana will have to rely for some years to come on foreign health professionals, she noted, UNAIDS is recommending appropriate courses for them about local culture, health policies and protocols. Many current staff will require crash courses on ARV treatment issues.

Testing, monitoring and surveillance of the Botswana AIDS plague, as many now call it, is carried out by the new Botswana-Harvard laboratory at the Princess Marina Hospital. The first of its kind anywhere in Africa, the laboratory, with a staff of 50, is equipped with gene sequencers and blood cell sorters, enabling scientists to keep track of the spread of HIV, especially the HIV-1C strain prevalent in Africa.

The lab will also conduct research for the development of new medicines, including a vaccine. "The virus strain in Botswana is clearly different from those we see in the West," said Dr. Max Essex, Chair of the Harvard AIDS Institute. "Nobody knows if a vaccine [being developed] against HIV-1B, the strain most common in Europe and the US, will work as well against HIV-1C." Scientists at the institute said they are concerned that strains like HIV-1C would become even more drug resistant without effective monitoring of patients taking ARVs. This is why, Dr. Khan said, the "buddy" system to ensure adherence is as important a component in the battle as further funds for training new medical teams.

Combining treatment and prevention

Botswana is supporting the new drug treatment policy with an expanded and more aggressive education campaign, modeled in part after Uganda, which has successfully reduced new HIV infections through sustained public education. President Mogae is determined to make sure that the message of free treatment gets out -- through radio, billboard campaigns and by word of mouth.

botswana hiv aids case study geography

Young Botswanan activists have been key in public AIDS education and prevention programmes.

Photo : ©UNAIDS / G. Pirozzi

Mr. Edmund Dladla, national coordinator of the Botswana Network of People Living With HIV/AIDS, welcomed the president's leadership. "Any person who is of working age, who has a job and some education talks about it. And everyone wonders about the impact AIDS is having, not only on those close to them, but also on the country as a whole. People are scared."

"For a decade," he continued, "until the end of the 1990s, we were in a state of denial, blaming the crisis on foreigners. Then, as we realized its extent, we started acting. Today, I would say the government is very transparent, pro-active and accountable. We are the most advanced African nation in this struggle -- and believe me, I would not have said that just three years ago."

Employers get involved

Botswana's private sector has also become involved. Three years ago, the country's biggest employer, the Debswana diamond mining company, realized after testing its 6,000-strong workforce that fully a third of workers aged between 24 and 40 were HIV-positive. With revenues of some $1.8 bn dollars a year, and skilled miners scarce, the company set up its own HIV/AIDS scheme.

"We realized we had to do something fast because diamonds are the foundation of our economy," said Ms. Tsetsele Fantan, director of the company's programme. She said Debswana agreed to provide free treatment for each infected employee and one legal spouse, while the government would provide treatment for other partners and their children. The government has also urged major banks, transport companies and even petrol stations to provide better levels of health care and make HIV counselling and treatment available to their employees.

The Harvard-Botswana lab is another example of the public-private partnerships the Botswana government is seeking to build. The government provided $3 mn, while additional funding was contributed by the Gates and Merck Foundations, the Bristol-Myers Squibb drug company, the Harvard AIDS Institute and others.

"This collaborative programme is designed to demonstrate the benefits of a comprehensive, multi-sectoral approach to improving the care of people living with HIV in a country with limited resources," said Dr. Clement Chela, of the Botswana Comprehensive HIV/AIDS Partnership. The fact that ARVs are now freely available, he added, has become a motivating factor for people to come forward. "The programme we have put in place here can work in other countries in Africa, and with international financial help, it can be sustained."

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With an adult HIV prevalence of 20.3 per cent. Botswana is ranked among the top four countries in the world most affected by HIV and AIDS behind South Africa, eSwatini and Lesotho. Among the 370,000 estimated people living with HIV in Botswana in 2018, 29, 500 were young people aged 15-24, the majority of them female (64 per cent). Of greater concern, three in every ten new HIV infections in Botswana in 2018 occurred among adolescents and young people aged 15 – 24 years. Young females in this age group were twice as likely to be newly infected than males the same age and adolescent girls 10-19 years were three times more likely to be infected than boys of the same age.

Botswana is on track to achieve the 90-90-90 treatment targets by 2020. At the end of 2018, 91% of people living with HIV knew their status, 92% of those were on ART and more than 95% of those on treatment were virally suppressed. This achievement however, masks the fact that young children living with HIV are being left behind in HIV treatment scale up and too few are being diagnosed and treated early to prevent HIV-related morbidity and mortality. The picture remains unclear for adolescents 10 – 19 years living with HIV on treatment.

While there is increased awareness of HIV in general, comprehensive knowledge of HIV remains low, condom use among sexually active young people is declining, and rates of forced sex and teenage pregnancy are ominously high. Transactional and age disparate sex, peer pressure, stigma and discrimination, harmful social and gender norms, gender inequality and unequal power dynamics contribute to the constrained progress in reducing new HIV infections amongst adolescents and young people. Furthermore, adolescent girls and young women continue to be disproportionately affected by the HIV epidemic, with early sexual debut, forced marriage and gender-based violence further increasing their vulnerability to acquiring HIV.

UNICEF’s Adolescents and HIV programme contributes to national efforts to prevent new HIV infections, specifically among adolescent girls and young women, provide treatment, care and support services to adolescents living with HIV, as well as to eliminate mother-to-child transmission of HIV. UNICEF is also contributing to efforts to scale up cutting-edge and youth-driven HIV interventions through collaboration with the National AIDS and Health Promotion Agency and the MTV Staying Alive Foundation.

A partnership has been established with the Ministry of Health and Wellness, Botswana Baylor Children’s Clinical Centre of Excellence, and civil society to implement and evaluate an intervention package for adolescents and young people living with HIV. It will involve a number of trainings on:

To strengthen youth participation and engagement, UNICEF in collaboration with NAPHA has introduced U-Report in Botswana, which is a social messaging platform designed to empower young people to speak out on issues that affect them. Furthermore, UNICEF is supporting government to establish a youth forum to facilitate and enhance meaningful engagement and participation.

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See full index, case study 6: hiv/aids in botswana flashcards preview, geography igcse > case study 6: hiv/aids in botswana > flashcards.

What are the causes of HIV/AIDS in Botswana? (education+sanitation)

Inadequate education: not taught methods of prevention. Contraceptives are scarce+expensive, so unprotected sex, so virus spreads. Low availability of healthcare.

What are the causes of HIV/AIDS in Botswana? (culture)

Polygamy: men have several sexual partners so increase chance of spreading. Women are seen as children producers so can’t have protected sex.

What are the causes of HIV/AIDS in Botswana? (economic)

Poverty: Not able to afford anti-retroviral drugs + forced into prostitution.

What has been the effects of HIV/AIDS in Botswana?

Life expectancy dropped from 74 to 30. Decrease in tourism. AIDS orphans+Shortage of skilled labour+reductions in wealth of family (due to paying medical care) lead to children dropping out education to work.

What is being done to manage HIV/AIDS in Botswana?

2002: first African country to provide condoms. (10,500 condom dispensers) Free HIV tests Anti-retroviral drugs given to 69% of infected adults. Education: ‘ABC’ Abstain, Be faithful, Condomize.

PSD for HIV/AIDS in Botswana

North-east districts have higher HIV rates. e.g. Sowa (66%)

Decks in Geography IGCSE Class (40):

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Search life-sciences literature ( 42,437,063 articles, preprints and more)

The geography of HIV/AIDS prevalence rates in Botswana.

Author information, affiliations.

HIV/AIDS (Auckland, N.Z.) , 18 Jul 2012 , 4: 95-102 DOI: 10.2147/hiv.s30537   PMID: 22870041  PMCID: PMC3411371

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Free full text , the geography of hiv/aids prevalence rates in botswana, ngianga-bakwin kandala.

1 University of Warwick, Warwick Medical School, Division of Health Sciences; Populations, Evidence and Technologies Group, Warwick Evidence, Coventry, UK

Eugene K Campbell

2 Department of Population Studies, University of Botswana, Gaborone, Botswana

Serai Dan Rakgoasi

Banyana c madi-segwagwe.

3 SADC Secretariat, Directorate of Social and Human Development and Special Programmes, Gaborone, Botswana

Thabo T Fako

4 Vice Chancellor’s Office, University of Botswana, Gaborone, Botswana

Botswana has the second-highest human immunodeficiency virus (HIV) infection rate in the world, with one in three adults infected. However, there is significant geographic variation at the district level and HIV prevalence is heterogeneous with the highest prevalence recorded in Selebi-Phikwe and North East. There is a lack of age-and location-adjusted prevalence maps that could be used for targeting HIV educational programs and efficient allocation of resources to higher risk groups.

We used a nationally representative household survey to investigate and explain district level inequalities in HIV rates. A Bayesian geoadditive mixed model based on Markov Chain Monte Carlo techniques was applied to map the geographic distribution of HIV prevalence in the 26 districts, accounting simultaneously for individual, household, and area factors using the 2008 Botswana HIV Impact Survey.

Overall, HIV prevalence was 17.6%, which was higher among females (20.4%) than males (14.3%). HIV prevalence was higher in cities and towns (20.3%) than in urban villages and rural areas (16.6% and 16.9%, respectively). We also observed an inverse U-shape association between age and prevalence of HIV, which had a different pattern in males and females. HIV prevalence was lowest among those aged 24 years or less and HIV affected over a third of those aged 25–35 years, before reaching a peak among the 36–49-year age group, after which the rate of HIV infection decreased by more than half among those aged 50 years and over. In a multivariate analysis, there was a statistically significant higher likelihood of HIV among females compared with males, and in clerical workers compared with professionals. The district-specific net spatial effects of HIV indicated a significantly higher HIV rate of 66% (posterior odds ratio of 1.66) in the northeast districts (Selebi-Phikwe, Sowa, and Francistown) and a reduced rate of 27% (posterior odds ratio of 0.73) in Kgalagadi North and Kweneng West districts.

This study showed a clear geographic distribution of the HIV epidemic, with the highest prevalence in the east-central districts. This study provides age- and location-adjusted prevalence maps that could be used for the targeting of HIV educational programs and efficient allocation of resources to higher risk groups. There is need for further research to determine the social, cultural, economic, behavioral, and other distal factors that might explain the high infection rates in some of the high-risk areas in Botswana.

The emergence and alarming spread of the human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) since the early 1980s have caused considerable concern about sexual and reproductive health among populations throughout the world, especially sub-Saharan Africa, which is home to 70 percent of the world’s HIV-infected people. 1

Southern Africa, particularly the Southern African Development Community, is the most affected region worldwide. 1 Botswana has the second-highest HIV infection rate in the world after Swaziland, 1 with one in three adults infected. In 2007–2009, the HIV prevalence among males and females aged 15–49 years in east, west, and central Africa was 2.1% and 3.0%, 4.5% and 6.7%, and 1.9% and 3.1%, respectively. 2 During the same period, HIV prevalence among males and females in Botswana was 18.9% and 28.9%, respectively. 2 Botswana’s HIV/AIDS epidemic is substantial in magnitude and impact; for example, 12% of children in Botswana have been orphaned due to AIDS. 1

While the impact of HIV/AIDS has been clear for all to see, estimating the population-based HIV prevalence rate has been a challenge for a number of years due to an absence of data. Subsequently, most estimates of HIV prevalence relied heavily on data derived from sentinel surveillance of pregnant women attending antenatal care.

Current estimates from the Department of HIV/AIDS Prevention and Care of HIV prevalence among pregnant women aged 15–49 years attending antenatal care in public health clinics in Botswana was 31.8%. 3 The national HIV prevalence amongst the women surveyed showed a decline in prevalence from 36.2% in 2001 to 31.8% in 2009. However, there is significant geographic variation at the district level, and HIV prevalence is heterogeneous in Botswana’s districts, with the highest prevalence recorded in Selebi-Phikwe and North East (41.6%). This is followed by Tutume (41.1%), Bobirwa (39.6%), and Chobe (39.3%). Hukuntsi has the lowest prevalence rate (16.1%). These HIV prevalence rates and those reported in the 2008 Botswana AIDS Impact Survey (BAIS III) 3 followed similar patterns, but mask significant variations within the population. Meanwhile, population-level socioeconomic and health resource characteristics have explained little of the variation in rates.

The success of any HIV/AIDS policy intervention depends on a broad and accurate understanding of the socioeconomic, environmental, and cultural factors that determine the spread of the disease. Until recently, available information on HIV prevalence was derived from antenatal clinics. However, information obtained from antenatal clinics represents only a small proportion of all cases in the general population, since many other cases do not seek medical attention in antenatal clinics. Thus, the antenatal clinics data may not be appropriate for estimating the prevalence of HIV for program developments.

Policy makers often want to know the distribution of HIV prevalence by geographical region, or association with environmental and cultural factors. In this regard, mapping risk variations in HIV rates is an invaluable tool. Further, the mapping of variation in risk of HIV rates can help improve the targeting of scarce resources for public health interventions.

The Geographic Information System (GIS) 4 is, therefore, a powerful tool for public health practitioners that easily aids assessment of patterns, trends, and relationships between health events and environmental, cultural, socioeconomic, and other geographic factors. GIS further helps us to understand HIV rates at the community level and assists with identifying underserved populations. It can also help public health agencies to efficiently allocate scarce program resources to appropriate locations, assist in identifying at-risk populations, and determine where to focus efforts to prevent HIV.

The benefits of using geostatistical methods combined with GIS are largely unknown and have not been investigated using the BAIS III data. This paper reports the results obtained using a nationally representative household survey by exploring the spatial distribution of HIV rates in Botswana, taking into account district-level factors. The BAIS III is the most recent AIDS impact survey conducted in Botswana and is a valuable resource for population-based HIV prevalence data.

To gain more understanding of the geographic variation or patterns based on the observed HIV rates, a Bayesian hierarchical model was fitted, with the inclusion of spatial (district), nonlinear metrical (age at HIV diagnosis) covariates, and other confounding risk factors such as employment. Of particular interest in this study was whether a significant geographic variation in HIV rates as observed in previous data existed, and, if so, what potential risk factors could explain such variation, taking into account population mobility and localized effects.

Data collection

The BAIS III is the third and latest of a series of nationally representative demographic surveys, conducted by the Botswana Central Statistical Office and funded by the Government of Botswana. Its aim was also to provide up-to-date information on the country’s HIV and AIDS epidemic.

The 2001 Botswana Population Housing Census 3 provided the sample frame for BAIS III, and ethical approval was obtained from the Botswana Ministry of Health. Overall, 16,992 eligible respondents aged 10–64 years (males and females) were identified from 7600 households, of whom 15,878 were successfully interviewed, yielding an individual response rate of 93%. For this study we did not consider ethical approval relevant because it was a secondary analysis of data. The sample population was treated anonymously and it was impossible to identify particular individuals.

Statistical analysis

We applied a Bayesian geoadditive semiparametric mixed model, a unified approach that explores geographic patterns in the prevalence of HIV infection and possible nonlinear effects within a simultaneous, coherent Bayesian regression framework. The model employed a fully Bayesian approach using Markov Chain Monte Carlo (MCMC) techniques for inference and model-checking. 5 The model and statistical techniques utilized have been described in more detail elsewhere. 6 , 7 The model is implemented in the BayesX (version 2.0.1; University of Munich, Munich, Germany) software package, which permits Bayesian inference based on MCMC simulation techniques. The statistical significance of apparent associations between potential risk factors and the prevalence of HIV was explored in chi-square and Mann–Whitney U -tests, as appropriate. A P -value of <0.05 was considered indicative of a statistically significant difference.

In the multivariate analysis, we evaluated the significance of the posterior odds ratio (POR) for the fixed, nonlinear, and spatial effects using the deviance information criterion as a measure of fit and model complexity. To account for possible departures from the assumed distribution, 95% credible regions for the PORs and probability maps (the equivalent of confidence intervals for the spatial effects) were calculated using robust standard errors estimated via MCMC simulation techniques. Although this estimation process is used less frequently in the literature, the estimated PORs that were produced could be interpreted as similar to those of ordinary logistic models.

Overall, HIV prevalence was 17.6%, which was higher among females (20.4%) than males (14.3%). HIV prevalence was higher in cities and towns (20.3%) than in urban villages and rural areas (16.6% and 16.9%, respectively) ( Table 1 ). We also observed an inverse U-shape association between age and the prevalence of HIV. HIV prevalence was lowest among those aged 24 years or less (5.6%) and reached over a third (33.2%) in those in the 25–35 year age group, before reaching a peak (37.1%) among those aged 36–49 years and then declining by more than half (16.9%) in those aged 50 years and over. The mean age of males was lower compared to females (25.1 years, standard deviation [SD] 19.3 years versus 27.2 years, SD 20.5 years) ( Table 1 ).

Prevalence and crude marginal odds ratio of HIV infection * by baseline characteristics 3

Abbreviations: BAIS III, 2008 Botswana AIDS Impact Survey; OR, odds ratio; CI, credible interval.

The unadjusted marginal ORs indicated that in 2008 the highest HIV prevalence was in Selebi-Phikwe followed by Sowa and Francistown. The lowest prevalence of HIV was observed in Kgalagadi North and Kweneng West districts. The districts were also ranked according to their respective HIV prevalence rates and the corresponding marginal odds ratios (ORs) ( Figure 1 ).

botswana hiv aids case study geography

HIV prevalence by district and marginal odds ratios, Botswana 2008.

The pattern of HIV prevalence did not differ markedly between districts in terms of marginal ORs and the prevalence rates, with consistently higher prevalence in Selebi-Phikwe, Sowa, and Francistown, and lower prevalence in Kweneng West district ( Table 1 ). The prevalence rates and marginal ORs of HIV at the district level indicated that 15 districts, namely Gaborone, Lobatse, Jwaneng, Ngwaketse West, Kweneng East, Central-Boteti, Kgatleng, Southern, Barolong, Ghanzi, Southeast, Kgatleng, Ngamiland North, Kgalagadi North, and Kweneng West, had HIV prevalence rates that were below the national prevalence ( Table 1 ).

The results of the multivariate analysis using Bayesian geoadditive regression analyses indicate that HIV rates were higher among females than males and among clerical jobholders than professionals, which are consistent with the unadjusted results ( Table 1 ). The district-specific net spatial effects of HIV, which include the total residual spatial effects of the district (ie, the sum of both the structured and unstructured spatial effects; see Table 1 ) indicated a statistically significant higher HIV rate of 66% (POR of 1.66) in the northeast districts (Selebi-Phikwe, Sowa, and Francistown) and a reduced rate of 27% (POR of 0.73) in Kgalagadi North and Kweneng West districts ( Figure 2 ). Two important observations emerged. First, after accounting for spatial dependencies of districts in the data, the districts with the highest HIV prevalence in the North East now included only Francistown and Selebi-Phikwe (not Sowa) while Gaborone remained the lowest prevalence district as suggested by the marginal OR ( Table 1 ). Second, there was a strong northeast–south gradient in these district effects, with a fairly sharp dividing-line running through the central districts. Over and above the impact of the fixed effects, there appeared to be a higher risk of HIV in the northeastern districts (North East, including Francistown, and Central Bobonong, including Selebi-Phikwe). This was quite general and affected most of the northeastern districts. Moreover, age at HIV diagnosis and district of residence were significant risk factors for HIV in Botswana.

botswana hiv aids case study geography

Total residual district spatial effects ( A ) and 95% posterior probability map ( B ) of the risk of HIV infection in Botswana. 3

Notes: ( A ) Red, high risk (OR: 1.66); green, low risk (OR: 0.73). ( B ) Black, positive spatial association (high risk); white, negative spatial association (low risk); grey, no spatial association.

Abbreviations: OR, odds ratio.

The estimated nonlinear effects of age at HIV diagnosis were plotted as PORs of the risk of HIV against age. Shown are the PORs together with the 95% point-wise credible intervals. There was a bell-shaped, nonlinear relationship between the risk of HIV and age. As expected, the likelihood of infection by age differed by sex, with males starting at the lowest probability, and attaining the peak later in life (40 years) than their female counterparts (peak at around 35 years old). At all other ages, the two estimates showed agreement in the increasing pattern of the probability of infection. A peak was observed between 30–40 years of age, when both males and females had the highest observed probability of HIV infection. Before age 30, this probability increased quickly as age increased. Beyond age 40 there was a declining probability of infection, although the variation in probability increased rapidly at the same time as age continued to increase ( Figure 3 ).

botswana hiv aids case study geography

Sex-specific nonlinear association of the risk of HIV and age at HIV diagnosis estimated from the data. 3

To the best of our knowledge, this study is the first to investigate inequalities at the district level using a nationally representative household sample and to take into account the effects of both individual and area based measures of social inequalities in order to provide insight into the influences of socioeconomic, environmental, and cultural factors on HIV prevalence in Botswana.

Our findings show that HIV rates in Botswana are indeed spatially distributed. While being female and working in a relatively low status of employment were associated with increased likelihood of HIV infection, the analysis also revealed significant district specific net spatial effects of HIV that could not be explained by sex, employment status, or rural–urban location. The associations between HIV risk and different socioeconomic indicators may have different implications and causes. For example, at the individual level, people of lower employment status may not have access to protective measures and health care. Meanwhile, professional people with higher education may have increased knowledge related to health promotion and increased compliance to prevention methods – although professionals with higher income may be at higher risk of HIV through engagement in risky sexual behaviors. 8 , 9

There was a higher proportion of males with an increase in seroprevalence at age 15 compared with females of the same age. A likely explanation is riskier intercourse among males. The percentage of adolescent males aged 15–19 years reporting condom use with their most recent sexual partner declined from 35% in 2000 to 31% in 2009, and only 38% reported that they could access condoms on their own. 6 As expected, females attained their highest peak of HIV risk 10 years earlier than males. These findings are probably due to the earlier sexual debut of males and early marriages among females compared with males. In other sub-Saharan African countries such as Zambia, it was found that respondents aged 15–19 years reporting sexual activity before age 15 were 27% in 2001/2002, compared with 16% in 2007. This decrease was probably due to HIV education.

While certain districts (Francistown, North East, and Selebi-Phikwe) had higher HIV prevalence, these results show that some aspect of HIV infection risk is spatial, such that districts that are in the proximity of these high prevalence districts also display elevated marginal ORs of HIV infection. Why certain districts have a higher risk of HIV infection is an area that has not been subjected to rigorous research. So while some districts are known to have a higher HIV prevalence, there is poor understanding of the contextual factors and other factors (sociocultural) that lead to these districts having a significantly higher prevalence and risk of HIV than others. However, it is well documented that geography is important at the area level. Living near a market place, for example, may be associated with increased HIV risk for young women, while living near roads connecting villages to cities increases the likelihood of migration from presumably conservative villages to more sexually permissive cities. 10 Living in rural areas may be associated with poor health care including HIV testing and treatment. The district-level relationship between employment status and HIV infection may be attenuated by socioeconomic heterogeneity.

The reasons why a district like Kweneng has the lowest HIV prevalence in the country are yet to be studied and therefore understood. This gap in knowledge of sociocultural and other context-specific factors that underpin the high HIV prevalence and risk in certain districts and lower rates in other districts, points to a clear need for research to attain an understanding of the socioeconomic, cultural, and other factors that might explain the significant differentials in risk of HIV infection in Botswana.

For example, Selebi-Phikwe and Sowa, the districts with the highest HIV prevalence, are both mining towns. Mining is a predominantly male occupation, and so it is likely to draw a lot of male labor from surrounding villages and other districts in the country, resulting in a separation of spouses, thus increasing the volume of migrants into the mining areas. Studies have presented evidence of statistical association between mining and HIV risk. 11 – 13 A study of a gold-mining community in South Africa found that miners had a significantly higher HIV prevalence rate than the wider community. 13 The study also found evidence of increased prevalence of syphilis, gonorrhea, and chlamydial infection, and low condom use, all of which could increase the spread of the virus. A similar study of underground miners in South Africa found that mine workers’ masculine identities render miners particularly vulnerable to HIV. 11 Palmer and colleagues documented a high HIV prevalence among gold miners in Guyana, which may provide a reservoir for the virus in this region. 12

Several factors may explain the relatively higher prevalence of HIV in Francistown, including the high cross-border traffic for trade and a high volume of both documented and undocumented migrants. A 2004 survey 14 indicated that AIDS awareness increased in Francistown and Mahalapye compared to previous years. However, condom use was higher in southern than in northern parts of Botswana. Not surprisingly, the prevalence of sexually transmitted infections (STIs) was lower in southern than northern Botswana. However, the report mentioned that consistent condom use was generally lower with regular partners than with casual ones.

Throughout the country, there was no relationship between condom use and number of sexual partners. Subsequently, the government commissioned a study of knowledge, attitude, and practice of youths on the topic of sexual and reproductive health. 15 The study revealed that almost 90% of males and females aged 15–24 years were aware of HIV, and almost all were aware of AIDS. However, while almost 90% of those aged 10–14 years were aware of AIDS (more so among females than males), less than 60% were aware of HIV (more so among males than females). Being aware of either HIV or AIDS implies knowledge about the relationship between the two. These differences indicate that levels of awareness about HIV and AIDS are lower among adolescents than the statistics suggest. Condom use was higher among males than females, regardless of whether sexual intercourse had occurred within a regular or casual relationship. Therefore, more plausible explanations of the observed pattern of higher HIV prevalence in the north and northeast could be attributed to differences in levels of condom use, STI prevalence, knowledge of HIV, and unmeasured factors that have geographic/spatial structures.

There is need for further research in order to define the factors that explain the high infection rates in some parts of Botswana. Smaller internal studies 16 have indicated evidence of lower rates of condom use and higher prevalence of STIs in the northern part of the country compared to the south. Other possible explanations for the relatively higher HIV prevalence and risk in districts along the east and northern parts of the country have centered on the proximity of such districts to countries such as Zimbabwe (to the east and northeast) and Zambia (to the north), where the HIV epidemic was first established before spreading to Botswana. The existence of major trucking routes such as Kazungula for access between southern and central Africa contributes further to the problem. This study therefore suggests a geospatial effect of HIV risk and spread across national boundaries.

Throughout the world, most HIV/AIDS prevention, treatment, and care programs have been managed with increasingly limited budgets, making it necessary for the limited resources to be deployed optimally and efficiently. A thorough understanding of the district-specific net spatial effects of HIV/AIDS can ensure that programs and interventions can achieve the greatest impact by focusing the limited resources in areas where there is the greatest risk of HIV infection.

Our findings indicate that public health interventions and health promotion for HIV prevention should take into account both individual and area variation. Planning and applying intervention measures could have different outcomes in terms of effectiveness in areas with a high degree of variability. Homogeneous policy intervention strategies may not give the required outcomes as suggested by large significant inequalities in HIV prevalence in our study.

It is worth mentioning some of the strengths and limitations of our study. The major strength is the use of a nationally representative household survey to investigate and explain district level inequalities in HIV rates using a novel approach that accounts simultaneously for individual, household, and area factors.

The main limitation of this study is the cross-sectional nature of the BAIS III data, which does not permit one to draw causal association between HIV prevalence and associated risk factors. Moreover, there is a time lag between exposure and detection of HIV infection. Therefore, an indicator such as employment status, which refers to the same period in which HIV was diagnosed, may not inform on exposures to HIV occurrence in earlier years.

The use of geographic area (district) as a single measure of area employment status is unlikely to provide a full assessment of area characteristics. Other factors that have not been included in the model may also explain inequalities in HIV prevalence (eg, environmental, socioeconomic, social and cultural factors, and access to health facilities and care). Finally, individual level measures of socioeconomic position, for instance, are not interchangeable in their relation to health outcomes and district-level factors.

This study is an extensive investigation of geographic variations of HIV in Botswana. Although inequalities in HIV prevalence have been reported in Botswana using sentinel antenatal care data, based on a large nationally representative population cross-sectional household survey, our study shows a clear significant geographic pattern of the epidemic noting individual (ie, age at diagnosis, sex, and employment status), area, and household factors (place of residence). The highest prevalence of infection was observed in the northeastern districts including Francistown and Selebi-Phikwe, but not Sowa district, while the prevalence of HIV in Gaborone remained significantly below the national average. Our study provides age- and location-adjusted prevalence maps that could be used for targeting HIV educational programs and efficient allocation of resources to higher-risk groups.

There is need for further research to unearth the social, cultural, economic, behavioral, and other factors that might explain the high infection rates in high-risk areas of Botswana. Therefore, further work is required using longitudinal studies to examine more closely the sociodemographic, behavioral, psychosocial, and distal factors (geographic location) as causal determinants of the risk of HIV/AIDS. In this regard, mixed methods using both quantitative and qualitative methods can be used to provide in-depth insights into the spatial dimension of the risk of HIV/AIDS.

The authors report no conflicts of interest in this work.

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Spatial Analysis of HIV Infection and Associated Risk Factors in Botswana

Associated data.

Data supporting the results can be obtained upon request from Ministry of Health and Wellness Botswana.

Botswana has the third highest human immunodeficiency virus (HIV) prevalence globally, and the severity of the epidemic within the country varies considerably between the districts. This study aimed to identify clusters of HIV and associated factors among adults in Botswana. Data from the Botswana Acquired Immunodeficiency Syndrome (AIDS) Impact Survey IV (BIAS IV), a nationally representative household-based survey, were used for this study. Multivariable logistic regression and Kulldorf’s scan statistics were used to identify the risk factors and HIV clusters. Socio-demographic characteristics were compared within and outside the clusters. HIV prevalence among the study participants was 25.1% (95% CI 23.3–26.4). HIV infection was significantly higher among the female gender, those older than 24 years and those reporting the use of condoms, while tertiary education had a protective effect. Two significant HIV clusters were identified, one located between Selibe-Phikwe and Francistown and another in the Central Mahalapye district. Clusters had higher levels of unemployment, less people with tertiary education and more people residing in rural areas compared to regions outside the clusters. Our study identified high-risk populations and regions with a high burden of HIV infection in Botswana. This calls for focused innovative and cost-effective HIV interventions on these vulnerable populations and regions to curb the HIV epidemic in Botswana.

1. Introduction

Although the first human immunodeficiency virus (HIV) case was identified almost four decades ago, it remains a significant public health issue, affecting approximately 36.7 million people globally [ 1 ]. Sub-Saharan Africa (SSA) bears the highest burden of HIV, accounting for approximately 70% of the total number of people living with HIV globally [ 2 , 3 ]. Despite the introduction of antiretroviral therapy (ART), HIV/Acquired Immune Deficiency Syndrome (AIDS) remains one of the leading causes of death in SSA [ 2 ]. There is increasing evidence suggesting that HIV epidemics are heterogenous and that HIV transmission is mostly concentrated within clustered micro-epidemics of varying geographical scales. To adequately mitigate the HIV/AIDS epidemic, it is imperative to employ geo-analytical methods to locate these clusters and understand the underlying determinants to optimise HIV prevention and treatment interventions currently in place [ 4 , 5 ].

Botswana, like most SSA countries, is battling a high burden of HIV. With a national prevalence rate of 23.7%, it has the third highest number of cases globally, with 13,800 newly diagnosed cases reported in 2017 [ 6 ]. The country introduced several interventions to fight the epidemic, including, but not limited to, ART, distribution of free condoms and safe male circumcision (SMC) [ 7 ]. The introduction of ART in 2002 increased the country’s life expectancy from 49 years in 2000 to 64 years in 2013 [ 8 ]. SMC was introduced to reduce HIV incidence and prevalence and by 2016, 42.7% of the targeted population had been circumcised [ 9 ]. These interventions contributed to the decline of the country’s prevalence rate from 26% in 2007 to 23.7% in 2017 [ 6 , 10 ]. However, varying prevalence rates have been reported across the districts over the past years. Some districts such as Chobe have experienced a decline in prevalence rates (from 29.4% in 2004 to 17.7% in 2013), while other districts such as Barolong and Kweneng East have shown an increasing trend (from 14.4% and 15.2% in 2004 to 20.3% and 21.5% in 2013, respectively) [ 11 ]. This sub-national variation in prevalence exists not only across districts but also between genders and age groups, indicating that Botswana’s current HIV prevalence is highly heterogenous [ 11 , 12 ]. The persistent high and varying geographic prevalence rates indicate that the one-size-fits-all approach to HIV prevention that the country has adopted is not effective, hence the need for a more effective geographical prioritization approach as recommended by the Joint United Nations Programme on HIV/AIDS [ 13 ].

To design effective HIV interventions requires an understanding of the spatial distribution of HIV prevalence and risk factors associated with HIV transmission. Previous studies have demonstrated that demographic and socio-economic factors are important predictors of HIV transmission in Botswana [ 12 , 14 , 15 ]. However, because of difficulties in obtaining geolocated HIV data, studies conducted in Botswana have mostly been conducted in large geographic units such as at the district level [ 15 ]. This coarse scale has necessitated assumptions about the characteristics, size and location of the study population, in the process masking important sub-area variation [ 16 ]. For instance, studies by Chomoyi and Musenge in Uganda [ 17 ] and Tanser et al. in KwaZulu Natal Province South Africa [ 16 ] were able to identify clusters, indicating the presence of micro-epidemics in otherwise generalised epidemics. These would not have been found without the use of a geo-spatial analytical approach; these studies have been instrumental in the implementation of geographically targeted, and comparatively cost-effective HIV interventions [ 18 ]. Botswana would greatly benefit from such focused interventions, especially considering that currently US$188 per capita, 44% of the country’s total health expenditure, is being spent on HIV and AIDS [ 19 ]. Therefore, we used the Botswana AIDS Impact Survey (BIAS) IV data and incorporated spatial analysis methods to investigate spatial heterogeneity of HIV prevalence in Botswana and identify risk factors associated with HIV infection.

2. Materials and Methods

2.1. study area.

The study was carried out in Botswana, a land-locked country in southern Africa that shares borders with South Africa, Zimbabwe, Zambia and Namibia and covers an area of about 582,000 km 2 . Botswana is divided into 10 administrative districts, and further divided into 28 sub-districts, also referred to as census districts (as of 2011). The Population and Housing Census of 2011 estimated Botswana’s population to be 2,024,904.

2.2. Study Data

A cross sectional study was conducted on a national population-based household survey, the Botswana AIDS Impact Survey IV (BIAS IV), which was carried out between January and April 2013. The survey is the latest of a series conducted by Botswana Central Statistics with the mandate to provide current HIV incidence and prevalence estimates as well as HIV knowledge in Botswana. The sample frame for the survey was provided by the 2011 Botswana Population and Housing Census, and a stratified two-stage sampling design was employed. The first stage involved random selection of primary sampling units, which were stratified by district and place of residence (urban/rural). In the second stage, an estimated 25 households per enumeration area were randomly selected, resulting in [ 20 ].

In the survey, a total of 9807 participants from the selected households aged 10–64 years were eligible to complete the individual questionnaire but only 8231 (83.9%) completed the survey. Demographic, sexual history and HIV/AIDS knowledge details of study participants were captured on a standardized questionnaire loaded on an Open Data Kit (ODK). Study participants who consented gave a dried blood spot sample which was later tested for HIV antibodies using the commercial HIV testing kits Vironostika and Murex.

The current study focused on adults ≥15 years of age and participants with missing data on covariates, HIV status and geolocation were excluded, giving a final study sample of 4708 participants.

2.3. Measures

The primary outcome variable for this study was HIV status, which was measured for all participants and divided into two categories—positive and negative. HIV predictor variables included socio-demographic factors—gender (male, female), age category (15–24, 25–34, 35–44, 45–54 and 55+ years), residence (urban, rural), marital status (never married, married/ever married), highest education level attained (none, primary, secondary, tertiary), religion (Christian, other) and employment (yes, no). HIV-related risk factors included alcohol use (yes, no) and condom use (yes, no). Data on these factors were considered based on the Joint United Nations Programme on HIV and AIDS (UNAIDS) guidelines for second-generation surveillance [ 21 ].

2.4. Statistical Analysis

Stata software version 14.1 (Stata Corp, College Station, TX, USA) was used to perform all statistical analyses. Sample weights accounting for complex survey design were incorporated in all calculations using the ‘svy’ module in Stata.

Standard descriptive statistics such as median and interquartile range for continuous variables and frequencies and proportions for categorical data were calculated to characterise HIV prevalence by socio-demographic and HIV-related risk factors. Univariate analysis using tabulation, a chi-square test and logistic regression were used to assess the association between covariates and HIV status. Multivariable logistic analysis was performed on covariates with p value < 0.1 in the univariate analysis. Unadjusted odds ratios (ORs) and adjusted odds ratios (AORs) and their 95% confidence intervals (CI) with a p -value < 0.05 were considered statistically significant results.

2.5. Spatial Analyses

The spatial units were the 28 census districts of Botswana as delineated by the 2011 Population and Housing Census. Census districts comprise the second administrative level in Botswana. Open data Kit with geographic information system (GIS) and global positioning system (GPS) technologies were used to collect the geographic coordinates (longitude and latitude) of the EAs. All study participants were geolocated as per their households. First, we calculated the crude estimation of HIV prevalence for all the 28 census districts and used the results to develop a choropleth map.

Second, spatial cluster analysis was done with Kulldorff’s scan statistic, using the SaTScan™ software [ 22 ]. The spatial scan statistic identifies statistically significant clusters using scanning windows (circular or elliptical) of varying sizes. These windows move around the study area to identify HIV-positive individuals within a window that is more than what is expected by chance. The relative risk (RR) of positive cases for each window is calculated using the observed number of positive and negative individuals within the windows [ 23 , 24 ]. The highest log-likelihood ratio (LLR) was calculated for each cluster to determine the most likely cluster. A Bernoulli Probability Model was used for this study because of the binomial outcome of interest (HIV-positive and -negative). We ran multiple analyses by setting the maximum spatial cluster size of 50%, 25%, 20% and 15% of the population at risk of HIV infection. The best cluster size was obtained at the maximum spatial cluster size of 25%. The statistically significant clusters with the radius of the scanning window, the number of observed and expected positives within the circle, RR, LLR and p value were saved for analysis and mapping. Socio-demographic characteristics of participants living within the cluster were compared against those living outside the clusters using a Chi-square test. All analyses were run using Monte Carlo replications of 999 for defining clusters and p < 0.05 was considered significant. The significant clusters obtained by SaTScan™ were mapped using ArcMap 10.5.1 (ESRI, Redlands, CA, USA).

3.1. Socio-Demographic and Behavioural Characteristics of Participants

Overall, 4708 participants were included in the analysis. Females made up 56.4% of the study participants, and the majority of participants (51.8%) were educated up to secondary level. Over half had never been married (56.1%) and 64.6% resided in urban areas (cities, towns and urban villages) ( Table 1 ). The prevalence of HIV among the study participants was 25.1% (95% CI 23.3–26.4).

Characteristics of study participants.

Note: a p -value for bivariate association between outcome and covariates (chi-square/two-sample t -test).

In the univariate analysis, gender, age, marital status, education level, employment and condom use were significantly associated with HIV status, while residence, alcohol use and religion were not statistically significant. After adjusting for all other variables included in the multivariable logistic regression model, independent predictors of increased odds of HIV infection were being female (adjusted odds ratio (AOR) = 1.42, 95% CI 1.16–1.73), being older than 24 years (e.g., AOR = 9.57, 95% CI 6.61–13.86 for age 35–44 vs. 15–24 years) and use of condoms over the past 12 months (AOR = 1.56, 95% CI 1.28–1.91). Having tertiary education was associated with reduced odds of HIV infection (AOR = 0.41, 95% CI 0.27–0.66) ( Table 2 ).

Univariate and multivariable logistic regression models of risk factors associated with human immunodeficiency virus (HIV) infection.

Note: † Odds ratio; ‡ Adjusted odds ratio; * Confidence interval.

3.2. Distribution of HIV Cases

The crude estimation of HIV prevalence ranged from 15.5% in Jwaneng district to 36.1% in Mahalapye district ( Figure 1 ). North East, Selibe-Phikwe and Bobonong districts also had high HIV prevalence—32.6%, 32.4% and 32.3% respectively ( Figure 1 ).

An external file that holds a picture, illustration, etc.
Object name is ijerph-18-03424-g001.jpg

Crude HIV prevalence in adults by district in Botswana.

3.3. Identification of Spatial Clusters in Botswana

The most likely cluster, cluster 1, was observed in the north-eastern region of Botwana and covers mostly Selibe-Phikwe and Francistown census districts as well as parts of Serowe/Palapye, North East and Central Bobonong census districts with a radius of 90.0 km. An RR of 1.47 ( p < 0.0001) was estimated, implying that those in the 519 locations in this cluster had 47% increased risk of HIV compared with those outside the cluster. A secondary cluster, cluster 2, with a radius of 4.89 km, was located in Central Mahalapye census district in the central part of Botswana. The estimated RR of 2.27 ( p = 0.004) implies that the population residing in the 34 locations within this cluster were 2.27 times more likely to be infected with HIV than those outside the cluster ( Figure 2 ). A comparative analysis of the characteristics of clusters and non-clusters showed that more participants inside the cluster resided in rural areas (48% vs. 32%) and were unemployed (52% vs. 44%). The cluster communities also had fewer participants with tertiary education (10% vs. 20%) ( Table 3 ).

An external file that holds a picture, illustration, etc.
Object name is ijerph-18-03424-g002.jpg

Clusters with high HIV prevalence in Botswana and summary statistics of significant clusters from SaTScan using a Bernoulli probability model.

Comparison of socio-demographic characteristics between participants within and outside the clusters.

4. Discussion

The study showed that the populations at greater risk of HIV infection were female, those aged older than 24 years and those who consistently used condoms in the past 12 months, while those with a higher education qualification were at lower odds of getting HIV. The scan statistics identified two HIV clusters independent of district boundaries, illustrating the presence of areas with high levels of HIV transmission in north-eastern Botswana census districts and Central Mahalapye census district.

Our results confirm that the HIV epidemic in Botswana is not ubiquitous but instead is characterised by geographically distinct clusters with disproportionately high numbers of people living with HIV. Cluster 1 covers a large area which encompasses a mining town, Selibe-Phikwe, the country’s second city Francistown and mostly villages in between and around these urban areas. Higher HIV prevalence in mining towns compared to other towns has been reported in southern African countries [ 15 ]. In their study, Carrel et al. observed a slowly shifting pattern of HIV prevalence increase in rural areas when compared with major cities in the Democratic Republic of the Congo between 2007 and 2013 [ 25 ]. They also found out that HIV prevalence increased rapidly in urban areas during the early stages of the HIV epidemic, before diffusing to rural areas. Further, proximity to the urban area was a determining factor for HIV spread into neighbouring areas [ 25 ], and this seems to be the case in the north-eastern parts of Botswana. Additionally, cluster 1 is located in close proximity to the country’s border with Zimbabwe, a country which also reports a high HIV prevalence rate, estimated at 16.7% in the 15–49 years age group [ 26 ]. The ongoing economic difficulties in Zimbabwe has prompted an influx of undocumented immigrants into the northern-eastern parts of Botswana and migration has been identified as a strong single predictor of high HIV prevalence and risk [ 27 , 28 ].

Cluster 2, on the other hand, is smaller, and found in a few suburbs in Mahalapye. Mahalapye is situated along a major national road, which also passes through cluster 1. Being half-way between the country’s capital city and Francistown (second city), Mahalapye is commonly used as a truck stop over by long-distance truck drivers. Studies have shown that long-distance truck drivers and people living in the vicinity of truck stops along major national roads are more at risk of contracting HIV when compared with the general population [ 29 ]. Our finding of identifying clusters along the national road is consistent with a study conducted by Tanser et al. in South Africa which identified clusters and high incidence of HIV along a national road [ 30 ].

Controlling for this spatial variability, our study reveals that women were at a higher risk of HIV infection in Botswana when compared with men. The findings are consistent with other studies conducted in SSA where HIV prevalence was found to be higher in females than males [ 2 , 26 ]. However, this is in contrast to findings in Western settings such as Australia, where women accounted for only 22% of new infections in 2017 [ 31 ]. In addition to biological factors, a wide range of economic and socio-cultural factors are responsible for increasing the vulnerability of African women to HIV infection [ 32 ]. To validate this, a study that examined sexual practices of ethnic groups in Botswana concluded that deeply rooted sexual norms and practices render women vulnerable to HIV infection, as these women do not have a say in pertinent sexual decisions such as the use of a condom [ 33 ]. Another factor that might contribute to males being less vulnerable in Botswana is SMC—an ‘add-on’ HIV prevention strategy that benefits men in Botswana. Studies from randomised control trials in Kenya, Uganda and South Africa have demonstrated that SMC can reduce the risk of acquiring HIV infection by 60% [ 34 ]. In addition to scaling up preventive strategies that protect women from HIV infection such as pre-exposure prophylaxis (PrEP), there is a need for the country to improve women’s economic and educational status [ 35 ]. Education has been found to increase opportunities for employment and gender equality for women which heightens their prospect of protection against HIV infection [ 32 ].

Our findings also show a significant association between HIV risk and increase in age. Those aged 15–24 years had a lower risk of HIV compared with older age groups. The current finding is in agreement with the results of a study that analysed BIAS III data [ 15 ]. The 25 years and above age group consists of those in their prime reproductive age, which could be associated with greater exposure to increased risk of HIV [ 36 ]. The reduced HIV risk in the 15–24 years age group could be the result of intensive age-focused strategies targeting this group, which was previously identified as having the highest transmission rates in Botswana [ 37 ]. ‘Life-skills’ education, a sexual risk reduction intervention, has been implemented as part of the curriculum in schools to increase adolescents’ HIV prevention skills and knowledge [ 38 ]. The continuing low HIV prevalence in this age group indicates the effectiveness of age-appropriate interventions, suggesting that such interventions should be given to older age groups to reduce the disease burden.

The observed protective association between tertiary education and risk of HIV infection suggests that increased knowledge and economic independence are vital in HIV prevention. A study conducted in Botswana found that even though HIV awareness was high in the population, HIV knowledge was quite low. HIV knowledge is crucial in adopting and maintaining behaviours related to reduced risk of HIV [ 14 ]. Another study conducted in Zambia found a significant association between educational attainment and testing for HIV, such that testing was high among educated women living in urban areas, with wealth index further strengthening the association [ 39 ]. These findings indicate that there is a need for HIV interventions targeting those with lower education attainment to reduce their risk of HIV infection. Letshwenyo-Maruatona et al. recommended inclusion of innovative technology such as Facebook and YouTube to disseminate HIV/AIDS information and improve HIV knowledge in the general population [ 40 ]. However, as a long-term measure, the Botswana government should review its policies and introduce structural interventions to improve educational attainment [ 6 ].

An unexpected observation was that of increased risk of HIV infection among participants who used condoms consistently over the previous 12 months. Consistent with these findings are those reported in the settings of Malawi and South Africa [ 36 , 41 ]. However, the high HIV prevalence in those who reported to be consistently using condoms could be linked to social desirability bias, such that participants felt compelled to state that they use condoms when in fact they did not [ 42 ]. One more possible explanation could be bias due to the use of condoms by those already infected in a bid to protect their partners [ 5 ]. Thus, we do not interpret these findings of our study as suggesting that not using a condom is truly associated with lower HIV risk, but that the link is attributable to bias or other factors not captured in the model. Previous studies have found that condom use has been declining over the years in Botswana and one of the reasons cited is misconceptions that SMC gives protection against HIV. In a study conducted in Botswana, Namibia and Swaziland, Andersson and Crockcroft discovered that one in six of circumcised men believed that it was appropriate for a circumcised man to assume sex without a condom [ 43 ]. Government needs to re-scale-up programs that encourage use of condom in conjunction with educational HIV prevention interventions that would dispel this misconception.

The results of our study justify the inclusion of a geo-spatial method for in-depth analyses of HIV epidemics and associated covariates. Knowing which population and where it is located is imperative in the design of tailored and effective interventions as well as estimating region-specific needs for ART and other related services. Our results therefore suggest that policy makers should pay more attention to the north-eastern and central census districts particularly rural villages in close proximity to urban areas (cities and towns) and national roads by upscaling age-specific HIV education and testing to initiate early ART. Additionally, there is a need to address the influx of undocumented migrants in the country especially in the northern parts of Botswana. With regards to HIV-associated factors, more resources and appropriate interventions need to be directed towards sub-populations with a high disease burden such as women, those aged 25 years and above and people with low educational attainment.

Strengths and Limitations

There are a number of limitations to this study. First, the data are quite old (2013), so trends of HIV might have changed. However, this is the latest national representative survey and the findings from this study can be useful for program management. Secondly, the study being a cross-sectional design limits the ability to draw conclusions concerning temporality and causality of the observed association between the HIV infection and predictor variables. Further, as the survey data on sexual behaviour were based on self-reporting, they are prone to recall and reporting bias as well as social desirability bias. Thirdly, unmeasured risk factors not adjusted for during data analysis might have contributed to the association between HIV prevalence and its association covariates. The fourth limitation to be considered when interpreting the study results is the circular nature of the SaTScan window, which at times does not work well where neighbourhood-level geographic barriers could not create non-circular interaction patterns. Even with these limitations, the use of the geostatistical approach, in addition to the statistical analysis using a nationally representative sample (BIAS IV), are the major strengths of this study. Importantly, we have identified high-risk areas of HIV in Botswana, which were not reported in earlier studies. This finding will be useful for focused targeting of prevention measures for control of HIV in Botswana.

5. Conclusions

The study findings affirm that the HIV epidemic in Botswana is heterogenous across the country. The associated covariates of HIV prevalence include women, older population and low educational attainment. These results have important implications for planning and prevention programs in Botswana. The government need to move from a homogenous approach in resource allocation and intervention strategy to spatially focused and high-risk groups to curb the spread of HIV in Botswana.


The authors would like to thank Ministry of Health and Wellness Botswana in allowing access to the raw data used in this study.

Author Contributions

Conceptualization, M.S. and K.W.; methodology, M.S. and K.W.; software, M.S. and K.W.; validation, M.S., K.W. and L.F.-K.; formal analysis, M.S. and K.W.; investigation, M.S.; resources, M.S.; data curation, M.S.; writing—original draft preparation, M.S.; writing—review and editing, K.W.; AND, L.F.-K.; visualization, M.S. and K.W.; supervision, K.W. and L.F.-K. All authors have read and agreed to the published version of the manuscript.

This research received no external funding however, L.F.-K. was supported by Australian National Health and Medical Research Council Early Career Fellowships (APP1158469).

Institutional Review Board Statement

Ethical approval was obtained from the Health Research Ethics Review Board of the Ministry of Health and Wellness, Botswana (Reference: HPDME 13/18/1) as well as The Australian National University Human Ethics Review Board (protocol 2020/611). The study was therefore in accordance with the ethical guidelines and requirements of human research ethics as specified by the above-mentioned review boards.

Informed Consent Statement

Not applicable. Secondary data was used.

Data Availability Statement

Conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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The impact of HIV/AIDS on education in Botswana

Since independence, Botswana has made great strides in economic and human development. In education, almost 100% of children now enrol in primary school, over 90% start secondary school and girls have enrollment rates similar to those of boys. However, Botswana's HIV epidemic is one of the world's most severe. The 2000 national antenatal survey of pregnant women found that 38.5% were HIV-positive and it is estimated that around one third of the adult population is infected. This presents a major challenge to further development and improvement in the accessibility and quality of education. The HIV/AIDS impact assessment commissioned by the Ministry of Education (MOE) and UNDP has explored implications for the education sector. This study looks at how HIV/AIDS affects the needs to be met by the education system and how will HIV/AIDS affect capacity to deliver education.

botswana hiv aids case study geography

Here’s a look at the origins, treatments and global response to HIV and AIDS.

HIV stands for human immunodeficiency virus.

AIDS stands for acquired immunodeficiency syndrome.

HIV/AIDS is spread through sexual contact with an infected person, sharing needles with an infected person, through transfusions of infected blood or through an infected mother.

People infected with HIV go through three stages of infection:

Acute infection, or acute retroviral syndrome, which can produce flu-like symptoms in the first month after infection.

Clinical latency, or asymptomatic HIV infection, in which HIV reproduces at lower levels.

AIDS, in which the amount of CD4 cells fall below 200 cells per cubic millimeter of blood (as opposed to the normal level of 500-1,500).

HIV-1 and HIV-2 can both cause AIDS. HIV-1 is the most common human immunodeficiency virus; HIV-2 is found mostly in western Africa.

Antiretroviral therapy (ART) involves taking a cocktail of HIV medications used to treat the virus. In 1987, Azidothymidine (AZT) became the first FDA-approved drug used to attempt to treat HIV/AIDS.

from UNAIDS:

38.4 million - Number of people living with HIV/AIDS worldwide in 2021.

5.9 million - Approximate number of people living with HIV globally that are unaware of their HIV-positive status in 2021.

160,000 - Newly infected children worldwide in 2021.

1.5 million - New infections worldwide in 2021.

650,000 - Approximate number of AIDS-related deaths worldwide in 2021.

Of the 4,500 new infections each day in 2019, 59% are in sub-Saharan Africa.

40.1 million - Approximate number of AIDS-related deaths worldwide since the start of the epidemic.

Sub-Saharan Africa is comprised of the following countries: Angola, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Democratic Republic of the Congo, Ivory Coast, Djibouti, Equatorial Guinea, Eritrea, Ethiopia, Gabon, The Gambia, Ghana, Guinea, Guinea-Bissau, Kenya, Lesotho, Liberia, Madagascar, Malawi, Mali, Mauritania, Mauritius, Mozambique, Namibia, Niger, Nigeria, Republic of the Congo, Rwanda, Sao Tome and Principe, Senegal, Seychelles, Sierra Leone, Somalia, South Africa, Sudan, South Sudan, Swaziland, Tanzania, Togo, Uganda, Zambia and Zimbabwe.

1981 - The Centers for Disease Control and Prevention (CDC) publish the first reports of men in Los Angeles, New York and San Francisco who were previously healthy and are suffering from rare forms of cancer and pneumonia, accompanied by “opportunistic infections.”

1982 - The CDC refer to the disease as AIDS for the first time.

1983 - French and American researchers determine that AIDS is caused by HIV.

1985 - Blood tests to detect HIV are developed.

December 1, 1988 - First World AIDS Day.

1999 - Researchers in the United States find evidence that HIV-1 most likely originated in a population of chimpanzees in West Africa. The virus appears to have been transmitted to people who hunted, butchered and consumed the chimpanzees for food.

January 29, 2003 - In his State of the Union speech, US President George W. Bush promises to dramatically increase funding to fight HIV/AIDS in Africa .

May 27, 2003 - Bush signs H.R. 1298, the US Leadership Against HIV/AIDS, Tuberculosis and Malaria Act of 2003, also known as PEPFAR (US President’s Emergency Plan for AIDS Relief), that provides $15 billion over the next five years to fight HIV/AIDS, tuberculosis and malaria abroad, particularly in Africa.

July 30, 2008 - H.R. 5501, The Tom Lantos and Henry J. Hyde United States Global Leadership Against HIV/AIDS, Tuberculosis, and Malaria Reauthorization Act of 2008, becomes law and authorizes up to $48 billion to combat global HIV/AIDS, tuberculosis and malaria. Through 2013, PEPFAR plans to work in partnership with host nations to support treatment for at least four million people, prevention of 12 million new infections and care for 12 million people.

October 2011 - In his book, “The Origins of AIDS,” Dr. Jacques Pepin traces the emergence and subsequent development of HIV/AIDS to suggest that initial AIDS outbreaks began earlier than previously believed.

July 24, 2012 - Doctors announce during the 19th International AIDS Conference that Timothy Ray Brown, known as the “Berlin patient,” has been clinically “cured” of HIV. Brown, diagnosed with leukemia, underwent a bone marrow transplant in 2007 using marrow from a donor with an HIV-resistant mutation. He no longer has detectable HIV.

March 3, 2013 - Researchers announce that a baby born infected with HIV has been “functionally cured.” The child, born in Mississippi, was given high doses of antiretroviral drugs within 30 hours of being born. A year later, the child now has detectable levels of the virus in her blood, 27 months after being taken off antiretroviral drugs, according to scientists involved with her case.

June 18, 2013 - Marking the 10th anniversary of PEPFAR, Secretary of State John Kerry announces that the millionth child has been born HIV-free due to prevention of mother-to-child transmission programs (PMTCT).

March 14, 2014 - The CDC reports on a case of likely female-to-female HIV transmission. Unlike previous announcements of other cases involving female-to-female transmission, this case excludes additional risk factors for HIV transmission.

July 24, 2017 - A 9-year-old child from South Africa is reported to have been in remission for over eight years without treatment, according to Dr. Avy Violari, who spoke at the 9th International AIDS Society Conference on HIV Science in Paris.

November 2018 - According to PEPFAR’s website, they have “supported life-saving antiretroviral treatment (ART) for more than 14.6 million men, women and children” since 2003.

March 5, 2019 - According to a case study published in the journal Nature , a second person has sustained remission from HIV-1. The “London patient” was treated with stem cell transplants from donors with an HIV-resistant mutation. The London patient has been in remission for 18 months since he stopped taking antiretroviral drugs. The study also includes a possible third remission after stem cell transplantation, this person is referred to as the “Düsseldorf patient.”

May 2, 2019 - A study of nearly 1,000 gay male couples, where one partner with HIV took antiretroviral therapy (ART), found no new cases of transmission to the HIV-negative partner during sex without a condom. The landmark, eight-year study, published in the Lancet medical journal shows that the risk of passing on the HIV virus is eliminated with effective drugs treatment.

October 7, 2019 - Governor Gavin Newsom signs a bill making HIV prevention drugs available without a prescription in California starting on January 1, 2020. The medications covered by the new legislation are pre-exposure prophylaxis (PrEP) and post-exposure prophylaxis (PEP), which both help prevent HIV infections. California becomes the first state in the country to allow pharmacists to provide the drugs without a physician’s prescription.

November 6, 2019 - According to a study published in the Journal of Acquired Immune Deficiency Syndromes, a team of scientists has detected a new strain of HIV. The strain is a part of the Group M version of HIV-1, the same family of virus subtypes to blame for the global HIV pandemic, according to Abbott Laboratories, which conducted the research along with the University of Missouri, Kansas City.

June 15, 2020 - A study is published in the journal JAMA Network Open showing that the life expectancy of people with HIV approaches that of people without the virus, when antiviral therapy is started early in infection. However, disparities still remain in the number of chronic health problems that people with HIV endure.

July 7, 2020 - Scientists presenting at the 23rd International AIDS Conference announce a new study that found an injection of the investigational drug cabotegravir every eight weeks was more effective at preventing HIV than daily oral pills. It is also announced that a Brazilian man might be the first person to experience long-term HIV remission after being treated with only an antiviral drug regimen – not stem cell transplantation.

November 16, 2021 - A new study finds a second patient whose body has seemingly rid itself of HIV. The international team of scientists reports in the Annals of Internal Medicine that the patient, originally from the city of Esperanza, Argentina, showed no evidence of intact HIV in large numbers of her cells, suggesting that she may have naturally achieved what they describe as a “sterilizing cure” of HIV infection. The 30-year-old woman in the new study is only the second patient who has been described as achieving this sterilizing cure without help from stem cell transplantation or other treatment.

December 20, 2021 - The US Food and Drug Administration announces that it has approved the first injectable medication for pre-exposure prophylaxis (PrEP) to lower the risk of getting HIV through sex.

February 15, 2022 - A US woman becomes the third known person to go into HIV remission, and the first mixed-race woman, thanks to a transplant of stem cells from umbilical cord blood, according to research presented at a conference on Retroviruses and Opportunistic Infections.

December 1, 2022 - An experimental HIV vaccine, called eOD-GT8 60mer, has been found to induce broadly neutralizing antibody precursors among a small group of volunteers in a Phase 1 study. The clinical trial results, published in the journal Science , suggest that a two-dose regimen of the vaccine, given eight weeks apart, can elicit immune responses against the human immunodeficiency virus.

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