Assessing the impact of agrochemicals on schistosomiasis transmission: A mathematical study
17 Apr 2021-International Journal of Biomathematics (World Scientific Publishing Company)-Vol. 14, Iss: 08
TL;DR: It is revealed that the agricultural pollution can enhance the transmission intensity of schistosomiasis, and in order to prevent the outbreak of schists disease, the use of pesticides should be controlled.
Abstract: Schistosomiasis is a snail-borne parasitic disease, which is affecting almost 240 million people worldwide. The number of humans affected by schistosomiasis is continuously increasing with the rise...
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TL;DR: Should past dependences of the global environmental impacts of agriculture on human population and consumption continue, 109 hectares of natural ecosystems would be converted to agriculture by 2050, accompanied by 2.4- to 2.7-fold increases in nitrogen- and phosphorus-driven eutrophication of terrestrial, freshwater, and near-shore marine ecosystems.
Abstract: During the next 50 years, which is likely to be the final period of rapid agricultural expansion, demand for food by a wealthier and 50% larger global population will be a major driver of global environmental change. Should past dependences of the global environmental impacts of agriculture on human population and consumption continue, 10(9) hectares of natural ecosystems would be converted to agriculture by 2050. This would be accompanied by 2.4- to 2.7-fold increases in nitrogen- and phosphorus-driven eutrophication of terrestrial, freshwater, and near-shore marine ecosystems, and comparable increases in pesticide use. This eutrophication and habitat destruction would cause unprecedented ecosystem simplification, loss of ecosystem services, and species extinctions. Significant scientific advances and regulatory, technological, and policy changes are needed to control the environmental impacts of agricultural expansion.
3,606 citations
TL;DR: This work develops methods for applying existing analytical tools to perform analyses on a variety of mathematical and computer models and provides a complete methodology for performing these analyses, in both deterministic and stochastic settings, and proposes novel techniques to handle problems encountered during these types of analyses.
2,014 citations
TL;DR: It is concluded that the development and management of water resources is an important risk factor for schistosomiasis, and hence strategies to mitigate negative effects should become integral parts in the planning, implementation, and operation of future water projects.
Abstract: An estimated 779 million people are at risk of schistosomiasis, of whom 106 million (13.6%) live in irrigation schemes or in close proximity to large dam reservoirs. We identified 58 studies that examined the relation between water resources development projects and schistosomiasis, primarily in African settings. We present a systematic literature review and meta-analysis with the following objectives: (1) to update at-risk populations of schistosomiasis and number of people infected in endemic countries, and (2) to quantify the risk of water resources development and management on schistosomiasis. Using 35 datasets from 24 African studies, our meta-analysis showed pooled random risk ratios of 2.4 and 2.6 for urinary and intestinal schistosomiasis, respectively, among people living adjacent to dam reservoirs. The risk ratio estimate for studies evaluating the effect of irrigation on urinary schistosomiasis was in the range 0.02-7.3 (summary estimate 1.1) and that on intestinal schistosomiasis in the range 0.49-23.0 (summary estimate 4.7). Geographic stratification showed important spatial differences, idiosyncratic to the type of water resources development. We conclude that the development and management of water resources is an important risk factor for schistosomiasis, and hence strategies to mitigate negative effects should become integral parts in the planning, implementation, and operation of future water projects.
1,933 citations
TL;DR: There is need for increased support for schistosomiasis control in the most severely affected countries, which are among the least developed whose health systems face difficulties to provide basic care at the primary health level.
1,292 citations
TL;DR: An uncertainty and a sensitivity analysis are described and applied based upon the Latin Hypercube Sampling (LHS) scheme, which is an extremely efficient sampling design proposed by McKay, Conover & Beckman (1979).
Abstract: Summary HIV transmission models have become very complex. The behavior of some of these models may only be explored by uncertainty and sensitivity analyses, because the structural complexity of the model are coupled with a high degree of uncertainty in estimating the values of the input parameters. Uncertainty analysis may be used to assess the variability (prediction imprecision) in the outcome variable that is due to the uncertainty in estimating the input values. A sensitivity analysis can extend an uncertainty analysis by identifying which parameters are important in contributing to the prediction imprecision (i.e., how do changes in the values of the input parameters alter the value of the outcome variable). In this paper an uncertainty and a sensitivity analysis are described and applied; both analyses are based upon the Latin Hypercube Sampling (LHS) scheme, which is an extremely efficient sampling design proposed by McKay, Conover & Beckman (1979). The methods described in this paper have not previously been applied to deterministic models of disease transmission, although these models have many characteristics in common with the risk assessment models that the strategies were designed to investigate. The utility of the LHS uncertainty and the LHS/PRC (Latin Hypercube Sampling/Partial Rank Correlation) sensitivity analysis techniques are illustrated by analyzing a complex deterministic model of HIV transmission.
1,127 citations