Environmental determinants of malaria transmission in African villages

Malaria transmission is complex, involving a range of hydroclimatological, biological, and environmental processes. The high degree of non-linearity in these processes makes it difficult to predict and intervene against malaria. This study seeks both to define a minimal number of malaria transmission determinants, and to provide a theoretical basis for sustainable environmental manipulation to prevent malaria transmission.

Using a field-tested mechanistic malaria model, HYDREMATS, a theoretical study was conducted under hypothetical conditions. Simulations were conducted with a range of hydroclimatological and environmental conditions: temperature (t), length of wet season (T_wet), storm inter-arrival time (T_int), persistence of vector breeding pools (T_on), and distribution of houses from breeding pools and from each other (X_dist and Y_dist, respectively). Based on the theoretical study, a malaria time scale, T_o, and a predictive theory of malaria transmission were introduced. The performance of the predictive theory was compared against the observational malaria transmission data in West Africa. Population density was used to estimate the scale that describes the spatial distribution of houses.

The predictive theory shows a universality in malaria endemic conditions when plotted using two newly-introduced dimension-less parameters. The projected malaria transmission potential compared well with the observation data, and the apparent differences were discussed. The results illustrate the importance of spatial aspects in malaria transmission.

The predictive theory is useful in measuring malaria transmission potential, and it can also provide guidelines on how to plan the layout of human habitats in order to prevent endemic malaria. Malaria-resistant villages can be designed by locating houses further than critical distances away from breeding pools or by removing pools within a critical distance from houses; the critical distance is described in the context of local climatology and hydrology.