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Sociodemographic context of the AIDS epidemic in a rural area in Tanzania with a focus on people's mobility and marriage
  1. J T Boerma1,
  2. M Urassa2,
  3. S Nnko2,
  4. J Ng'weshemi2,
  5. R Isingo2,
  6. B Zaba3,
  7. G Mwaluko2
  1. 1Department of Epidemiology, School of Public Health, and Carolina Population Center, University of North Carolina, USA
  2. 2Tanzania–Netherlands Project to Support AIDS control in Mwanza Region
  3. 3London School of Hygiene and Tropical Medicine, Keppel St, London WC1, UK
  1. Correspondence to:
 Dr J Ties Boerma, Department of Epidemiology, School of Public Health, and Carolina Population Center, University of North Carolina, Chapel Hill, NC 27516-3997, USA;


This analysis focuses on how sociocultural and economic characteristics of a poor semi-urban and rural population (Kisesa ward) in north west Tanzania may directly and indirectly affect the epidemiology of HIV and other sexually transmitted infections (STI). Poverty and sociocultural changes may contribute to the observed high levels of marital instability and high levels of short and long term migration in Kisesa, especially among younger adults. Marriage and migration patterns are important underlying factors affecting the spread of HIV. The most cost-effective intervention strategy may be to focus on the trading centre in which mobility is higher, bars were more common, and HIV prevalence and incidence were considerably higher than in the nearby rural villages. If resources suffice, additional work can be undertaken in the rural villages, although it is not clear to what extent the rural epidemic would be self sustaining if the interventions in the trading centre were effective.

  • AIDS
  • sexually transmitted disease
  • demography
  • Tanzania

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  • * The HIV incidence rate can be treated analogously to the central death rate, nMx, in a life table, as it is a ratio of events to persons years at risk. In life table terms, the age pattern of stable prevalence associated with a given regime of incidence rates is given by the complement of the proportionate person years function ((1−nLx)/n). Obtaining the person years nLx function from the central rate, nMx, is a standard straightforward calculation, provided we can make some simplifying assumptions about the linearity of change with age in the proportion of susceptibles, lx, in the population—within the narrow two and three year age intervals considered here, such an assumption is justified.