Muizenberg

MMED 2016

Seventh annual Clinic on Meaningful Modeling of Epidemiological Data

African Institute for Mathematical Sciences, Muizenberg, Cape Town, South Africa
May 30 - June 10, 2016

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HIV and TB Co-Infection in Madagascar

Overview

The co-epidemic of HIV and tuberculosis is a widely acknowledged global health challenge. In some localities, HIV infection has been shown to double the risk of activating individuals with latent TB infection to active TB, which is the infectious and diseased state that can cause death. Madagascar represents one of the few countries in Sub-Saharan African where HIV-prevalence remains under 1%, though tuberculosis infection is markedly widespread and increasing. Madagascar’s HIV screening programs have been minimal in recent years, and the extent to which increasing TB notifications might be due to unreported increases in the burden of HIV infection have been unexplored.

This group will have the opportunity to address the following aims (starting with the first and proceeding to the second only on completion of the first):

  • Using publicly-available country-level prevalence data for HIV from UNAIDS, the group will build on a model described in Williams et al. 2009 to estimate incidence for HIV and TB from HIV prevalence over a 15 year time series for Madagascar. Key to this analysis is an understanding of the TB:HIV incidence rate ratio (IRR), which describes the incidence of TB in HIV-positive (not on ART) people divided by the incidence of TB in HIV negative people. HIV-driven estimates of the annual TB notification rate from our model will then be evaluated against country-level TB data from the WHO Stop TB program.
  • Using a shorter-term (2013-2014), geo-referenced dataset from the Madagascar Ministry of Public Health, the group will then map the spatial extent of current patterns in HIV and TB incidence in Madagascar. Regional HIV and TB estimates for Madagascar’s 110 districts will be evaluated against the model outlined in Aim 1 to assess the extent to which nation-wide trends are recapitulated locally. These spatially aggregated data distinguish between pulmonary and extrapulmonary forms of TB, which will enable quantitative estimates of the Madagascar-specific TB:HIV IRR since extrapulmonary forms of TB are rare in HIV-negative individuals.

Things to consider

This group is recommended for:

  • Participants who are interested in HIV.
  • Participants who are interested in working with data.
  • Participants who are interested in developing population-level models.
  • Participants who are interested in the dynamics of coinfection.

This group will have the opportunity to engage in any of the following:

  • Work with publicly available data from WHO, UNAIDS, and the World Bank
  • Clean and analyze a country-level dataset for HIV/TB obtained from the Ministry of Public Health, Madagascar
  • If desired: Publish the analysis of existing data and explore whether additional clinical work will be needed to more accurately assess current HIV incidence in Madagascar

  • Potential group members are encouraged to review the following sessions before before Week 2:
    • Introduction to model implementation (Tuesday AM)
    • Introduction to models and data: HIV in Harare (Tuesday AM/PM)
    • Introduction to likelihood (Thursday PM)
    • Likelihood fitting and dynamic models I (Friday AM)
  • In addition the following sessions during Week 2 will be essential for this group:
    • Likelihood fitting and dynamic models II (Monday PM)
    • Introduction to Markov Chain Monte Carlo (Tuesday AM)

Background

The Joint United Nations Programme on HIV/AIDS (UNAIDS) has set a global target “90-90-90” for year 2020, by which 90% of HIV-positive people should know their status, 90% of these informed patients should be taking ART and 90% should have fully suppressed viral loads. UNAIDS aims to end the AIDS epidemic by 2030, which they have defined as achieving a global rate of fewer than one new infection and one AIDS death per thousand adults. As such, it is critical that the landscape of HIV incidence be well-elucidated, especially in southern Africa, where 36% of all HIV-positive adults (but only 1.6% of the global adult population) live. Though HIV prevalence in Madagascar has, historically, been low in comparison with other Southern African nations, sexually transmitted diseases, such as syphilis, abound (citation needed). A rapidly rising TB notification rate in two provinces where sex work is common could be driven by HIV.

The last formal analysis of HIV prevalence and incidence in Madagascar took place in 1996, when the nationwide prevalence was <1% but rising. At the time, projection models predicted that HIV seroprevalence would continue to rise in the ensuing decades, reaching rates of 3-15% of the population by 2015 (Behets et al 1996). The extent to which HIV prevalence rates have tracked these projections remains unclear; country-level reporting suggests that seroprevalence remains <1%, but more fine scale district-level data may reveal other patterns.

Data

  • WHO Stop TB program data on both HIV and TB for Madagascar (http://www.who.int/tb/country/data/download/en/)
  • World Bank TB notification rate data for Madagascar (http://data.worldbank.org/indicator/SH.TBS.INCD)
  • District-level HIV data from the Ministry of Public Health, Madagascar
  • Publicly available country-level GIS data for Madagascar (http://www.mapcruzin.com/free-madagascar-arcgis-maps-shapefiles.htm)

Resources

References

Tutorials