The role of migration networks in the development of Botswana’s generalized HIV epidemic

  1. Janet Song
  2. Justin T Okano
  3. Joan Ponce
  4. Lesego Busang
  5. Khumo Seipone
  6. Eugenio Valdano
  7. Sally Blower

  • Curated by eLife

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    This valuable paper uses representative samples of micro-census data from Botswana to describe migration rates over four points in time, from 1981 to 2011. The authors use compelling descriptive data to present migration characteristics where roughly 10% of the population moved in the past year - with equal numbers of men and women, and with migration between districts more common than within districts. Preliminary data indicated migration patterns could have supported HIV diffusion, this can be a starting point for more in-depth analyses. The work will be of interest to those studying human movement and its impact on diseases.

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Abstract

The majority of people with HIV live in sub-Saharan Africa, where epidemics are generalized. For these epidemics to develop, populations need to be mobile. However, the role of population-level mobility in the development of generalized HIV epidemics has not been studied. Here we do so by studying historical migration data from Botswana, which has one of the most severe generalized HIV epidemics worldwide; HIV prevalence was 21% in 2021. The country reported its first AIDS case in 1985 when it began to rapidly urbanize. We hypothesize that, during the development of Botswana’s epidemic, the population was extremely mobile and the country was highly connected by substantial migratory flows. We test this mobility hypothesis by conducting a network analysis using a historical time series (1981–2011) of micro-census data from Botswana. Our results support our hypothesis. We found complex migration networks with very high rates of rural-to-urban, and urban-to-rural, migration: 10% of the population moved annually. Mining towns (where AIDS cases were first reported, and risk behavior was high) were important in-flow and out-flow migration hubs, suggesting that they functioned as ‘core groups’ for HIV transmission and dissemination. Migration networks could have dispersed HIV throughout Botswana and generated the current hyperendemic epidemic.

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  1. Version published to 10.7554/elife.85435 on eLife
  2. eLife

    Author Response

    We thank the Editor for his assessment. We agree that the data we present in this manuscript can be a starting point for more in-depth analysis. We are currently developing a mathematical model of HIV transmission dynamics; we plan to use the data that we present in this paper as parameter values.

    Reviewer #1 (Public Review):

    One aim of this paper was to study historical migration from Botswana during the time of the development of the HIV epidemic. The second aim was to test whether the migration networks impacted the development of the epidemic. The first aim was achieved: this paper used historical census data in a clear way, to describe the qualities of characteristics of migration in the country at four points in time, from 1981 to 2011. Very detailed data are presented in clear ways, using network chord diagrams, sharing age- and sex-specific migration rates, and urban-rural classifications. However, data was not presented to achieve the second aim. The authors reviewed some important literature about migration and HIV. They suggested that the migration patterns, such as from specific mining towns and mostly between districts, could have been important in supporting the generalized spread of HIV. But without evidence linking HIV prevalence over time in the linked districts in Botswana, this aim was not supported.

    We have now made it clear that we are not testing whether the migration networks impacted the development of Botswana’s HIV epidemic: this is what the Reviewer describes as the second aim of our paper. We have only one aim: to test the hypothesis that, during the development of Botswana’s HIV epidemic, the population was extremely mobile and highly connected through migratory flows and counter-flows. This is based on the fact that these conditions are necessary for the development of a generalized HIV epidemic. However – previous to our analysis – these conditions have not been shown to occur during the development of a generalized HIV epidemic. Given that our results support our mobility hypothesis (i.e., that the population was very mobile and essentially all the districts were connected throughout the country), in the discussion (lines 338-362) we describe how the migration networks that we have identified may have impacted the development of the generalized hyperendemic HIV epidemic in Botswana. We have also clarified that our study has only one hypothesis that we are testing by referring to this single hypothesis as the mobility hypothesis (Abstract: lines 25-29).

    One other limitation of the paper was that very little context, outside of migration rates, was provided. Is there any additional information about economic growth, or political event for example, that could clarify or add context to these migration flows? As it stands now, these analyses are quite basic and don't take into account underlying demographic, economic, or political trends.

    In response to this concern we have expanded the text in the introduction to provide more context regarding political, demographic and economic factors (Introduction: lines 66-75). We have also expanded our discussion of the implications of our results (and of additional results that we have included: lines 263-283) for understanding the role of internal migration on urbanization in Botswana (Discussion: lines 379-420); urbanization occurred simultaneously to the development of Botswana’s generalized hyperendemic HIV epidemic.

    The data presented in this paper has potential impact. As the paper stands now, it could be quite useful for future work when linked to additional data sources on HIV prevalence over time (or other questions that could have been influenced by migration patterns).

    We thank this Reviewer for their helpful comments.

    Reviewer #2 (Public Review):

    To provide context into the HIV epidemic in Botswana over the latter half of the 20th century and the beginning of the 21st, the authors have analyzed micro census data to examine patterns of migration. They use this dataset to show how patterns between urban and rural areas have changed over several decades, and the demographic characteristics of migrants. The dataset used for this study is a very reliable source, and the insights in terms of migration patterns are interesting. The primary weakness of the analyses regards the link to HIV transmission: micro-census data only examine mobility that leads to individuals changing residence for longer periods of time, without accounting for shorter-term trips that may also lead to HIV transmission, such as seasonal migration or short trips. This is likely less of an issue with HIV than other diseases, however, due to its transmission often involving new sexual partners, which will generally be less likely to occur during short trips. Broadly, however, this is an interesting report on the migration patterns during a critical period for HIV transmission nationwide.

    We thank the Reviewer for their comments.

    In our current manuscript, we have discussed the potential impact of mobility on Botswana’s HIV epidemic, and focused on migration, i.e., one directional movement in terms of a permanent re-location of residency. This type of migration, by changing an individual’s sexual network and social environment, has been shown to increase the risk of acquiring HIV for both women and men. Short-term mobility (e.g., short-term circular migration, where the trip can range in duration from overnight to an entire season) can also affect HIV transmission dynamics. Circular migrants have been shown to both have an increased risk of acquiring HIV, and of transmitting HIV. The greater the number of trips and/or the duration of the trip, the greater the risk. We note that both migration and short-term mobility are important, and their relative importance to each other is likely to evolve over time as a generalized HIV epidemic diffuses through the population. Their relative importance is also likely to vary amongst countries in sub-Saharan Africa.

    We have added all of the previous paragraph, with citations, to the text (Discussion: lines 364-377).

  3. eLife

    eLife assessment

    This valuable paper uses representative samples of micro-census data from Botswana to describe migration rates over four points in time, from 1981 to 2011. The authors use compelling descriptive data to present migration characteristics where roughly 10% of the population moved in the past year - with equal numbers of men and women, and with migration between districts more common than within districts. Preliminary data indicated migration patterns could have supported HIV diffusion, this can be a starting point for more in-depth analyses. The work will be of interest to those studying human movement and its impact on diseases.

  4. eLife

    Reviewer #1 (Public Review):

    One aim of this paper was to study historical migration from Botswana during the time of the development of the HIV epidemic. The second aim was to test whether the migration networks impacted the development of the epidemic. The first aim was achieved: this paper used historical census data in a clear way, to describe the qualities of characteristics of migration in the country at four points in time, from 1981 to 2011. Very detailed data are presented in clear ways, using network chord diagrams, sharing age- and sex-specific migration rates, and urban-rural classifications. However, data was not presented to achieve the second aim. The authors reviewed some important literature about migration and HIV. They suggested that the migration patterns, such as from specific mining towns and mostly between districts, could have been important in supporting the generalized spread of HIV. But without evidence linking HIV prevalence over time in the linked districts in Botswana, this aim was not supported.

    One other limitation of the paper was that very little context, outside of migration rates, was provided. Is there any additional information about economic growth, or political event for example, that could clarify or add context to these migration flows? As it stands now, these analyses are quite basic and don't take into account underlying demographic, economic, or political trends.

    The data presented in this paper has potential impact. As the paper stands now, it could be quite useful for future work when linked to additional data sources on HIV prevalence over time (or other questions that could have been influenced by migration patterns).

  5. eLife

    Reviewer #2 (Public Review):

    To provide context into the HIV epidemic in Botswana over the latter half of the 20th century and the beginning of the 21st, the authors have analyzed micro census data to examine patterns of migration. They use this dataset to show how patterns between urban and rural areas have changed over several decades, and the demographic characteristics of migrants. The dataset used for this study is a very reliable source, and the insights in terms of migration patterns are interesting. The primary weakness of the analyses regards the link to HIV transmission: micro-census data only examine mobility that leads to individuals changing residence for longer periods of time, without accounting for shorter-term trips that may also lead to HIV transmission, such as seasonal migration or short trips. This is likely less of an issue with HIV than other diseases, however, due to its transmission often involving new sexual partners, which will generally be less likely to occur during short trips. Broadly, however, this is an interesting report on the migration patterns during a critical period for HIV transmission nationwide.

  6. Version published to 10.1101/2023.02.01.23285339v1 on medRxiv