Assessing the effects of global warming and local social and economic conditions on the malaria transmission

Abstract

ObjectiveTo show how a mathematical model can be used to describe and to understand the malaria transmission. MethodsThe effects on malaria transmission due to the impact of the global temperature changes and prevailing social and economic conditions in a community were assessed based on a previously presented compartmental model, which describes the overall transmission of malaria. Results/ConclusionsThe assessments were made from the scenarios produced by the model both in steady state and dynamic analyses. Depending on the risk level of malaria, the effects on malaria transmission can be predicted by the temperature ambient or local social and-economic conditions. Resumo

A mathematical model for malaria transmission relating global warming and local socioeconomic conditions

“…Sensitivity analysis is used to this assessment, taking into account the values for the parameters of the model presented in Table 1 can be performed with equation (9). This equation takes into account the contributions of each parameter to the variance of the basic reproduction ratio.…”

“…In a subsequent study 9 the previously developed model was used to assess the effects of global warming and local socioeconomic conditions on malaria transmission. These effects were assessed analyzing the equilibrium points calculated at different but fixed values of the parameters of the model.…”

“…And, evidently, temperature-dependent parameters ρ, µ' and α' are considered here as being associated to temperature changes. 9 Also, three representative risk areas for malaria are considered by assigning particular values for the inoculation h and transmission f rates.…”

Climate, environmental and socio-economic change: weighing up the balance in vector-borne disease transmission

“…Mathematical models of pathogen population dynamics, by virtue of their ability to provide a quantitative means for integrating and simulating the impacts of multi-factorial and multi-scale disease transmission processes, may offer us a particularly pertinent methodological tool for developing such holistic predictive and investigative frameworks [7][8][9][10][11][12][13]19,25,27,[42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][57][58]. Recent advances in incorporating the effects of climate, as well as anthropogenic alterations of ecosystems (e.g.…”

“…via induced changes in vector biodiversity [59], population movements and immunity [60,61], socioeconomic development and the effects of public health interventions), with disease transmission [25,62] make these tools even more applicable as quantitative frameworks for capturing the full range of community vulnerabilities to VBD transmission as a result of global climate change. Such models, by careful elaboration and inclusion of nonlinear functional relationships between biological and nonbiological social components of disease transmission, may also represent the only means by which the full complexity (emergence, self-organization, points of bifurcation and regime shifts) of the response of a natural -human system to global change may be explored [25,62]. In addition, new data-model assimilation frameworks provide a means for such models to capture and incorporate local social, ecological and climatic conditions, thereby affording the examination of the impacts of these proximate causes within the broader context of global climate change [42,63,64].…”