Environmental determinants of malaria transmission in African villages

Abstract

BackgroundMalaria 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.MethodsUsing 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 (Twet), storm inter-arrival time (Tint), persistence of vector breeding pools (Ton), and distribution of houses from breeding pools and from each other (Xdist and Ydist, respectively). Based on the theoretical study, a malaria time scale, To, 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.ResultsThe 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.ConclusionsThe 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-016-1633-7) contains supplementary material, which is available to authorized users.

Environmental Determinants of Malaria Transmission Around the Koka Reservoir in Ethiopia

“…Around this range of temperature, a small increase in temperature enhances malaria transmission potential significantly. For example, with a temperature increase from 20 to 23 ∘ C, the EIP reduces from 27.8 days to 15.9 days for Pf and from 19.1 days to 12.4 days for Pv (Endo & Eltahir, 2016;Paaijmans et al, 2009). The importance of the minor mosquito season on malaria transmission is also demonstrated in the data on observed malaria cases ( Figure S6).…”

“…The Koka Reservoir changes its water levels by approximately 6 m annually from 1,589.5 masl to 1,595.5 masl (Figure 3f ), which corresponds to about 0.3 to 1.2 km of the change in shoreline depending on location (Figure 2). The proximity of vector breeding pools to human habitats is an important factor both in increasing the abundance of mosquitoes and malaria transmission (Bomblies, 2014;Cano et al, 2006;Endo & Eltahir, 2016;Gu et al, 2006;Minakawa et al, 1999Minakawa et al, , 2002van der Hoek et al, 2003). Both mosquitoes' reproductive activities and malaria transmission require mosquitoes to encounter breeding pools and humans.…”

“…Closer proximity of a village to a reservoir is associated with higher number 10.1002/2017GH000108 of annual malaria cases because mosquitoes' lifetime flight distance limits malaria transmission far away from their breeding sites (Bomblies, 2014;Cano et al, 2006;Endo & Eltahir, 2016;Gu et al, 2006;Minakawa et al, 2002;Trape et al, 1992;van der Hoek et al, 2003;Zhou et al, 2007). For example, around the Koka Reservoir (N8 ∘ 25 ′ ; E39 ∘ 05 ′ ) in Ethiopia, the annual malaria case rates among people living within 1 km of the reservoir was 2.9 times greater than those living between 1 and 2 km from it, and 19.9 times greater than those living 5 to 9 km from it (Kibret et al, 2009).…”

Increased risk of malaria transmission with warming temperature in the Ethiopian Highlands

“…(Basic Reproduction Rate (R o )) The spatiallyexplicit approach of HYDREMATS allows for the estimation of R o accurately with minimal assumptions, which presents a significant advantage over the conventional Ross-MacDonald formula [6]. The basic reproduction number (R o ) is the most important and commonly used indicator of disease transmission potential; yet despite the importance and the popularity of this metric, accurate estimation of R o for malaria transmission has not been easy.…”

“…Pronounced increases in malaria have been reported widely over the East African Highlands in the late 20th century [1][2][3][4]. Malaria transmission in highland areas is generally limited by temperatures due to the thermal biology of malaria parasites and aquatic-stage vectors, but these limitations quickly diminish as temperature climbs [4][5][6]. The increased malaria transmission over the East African Highlands has been explained by observed warming [7][8][9], while other studies explain the surge of malaria by an increase in climate variability [10][11][12], or other factors such as drug resistance, land-use change, and population migration [13].…”