Retrospective data analyses of social and environmental determinants of malaria control for elimination prospects in Eritrea

Abstract

Background: The present study focuses on both long-and short-term malaria transmission in Eritrea and investigates the risk factors. Annual aggregates of information on malaria cases, deaths, diagnostics and control interventions from 2001 to 2008 and monthly reported data from 2009 to 2017 were obtained from the National Malaria Control Programme. We used a generalized linear regression model to examine the associations among total malaria cases, death, insecticide-treated net coverage, indoor residual spraying and climatic parameters. Results: Reduction in malaria mortality is demonstrated by the milestone margins of over 97% by the end of 2017. Malaria incidence likewise declined during the period (from 33 to 5 per 1000 population), representing a reduction of about 86% (R 2 = 0.3) slightly less than the decline in mortality. The distribution of insecticide treated nets generally declined between 2001 and 2014 (R 2 = 0.16) before increasing from 2015 to 2017, while the number of people protected by indoor residual spraying slightly increased (R 2 = 0.27). Higher rainfall was significantly associated with an increased number of malaria cases. The covariates rainfall and temperature are a better pair than IRS and LLIN to predict incidences. On the other hand, IRS and LLIN is a more significant pair to predict mortality cases. Conclusions: While Eritrea has made significant progress towards malaria elimination, this progress should be maintained and further improved. Distribution, coverage and utilization of malaria control and elimination tools should be optimized and sustained to safeguard the gains made. Additionally, consistent annual performance evaluation of malaria indicators would ensure a continuous learning process from gains/threats of epidemics and resurgence in regions already earmarked for elimination.

Dynamic evaluation and prediction of the ecological environment quality of the urban agglomeration on the northern slope of Tianshan Mountains

“…By verifying whether there is overlap of information among the 11 indicators, to ensure the accuracy of the evaluation results. Therefore, this study uses the method of multicollinearity diagnosis to make judgments (Mihreteab et al, 2020). Commonly used diagnostic indicators of multivariate collinearity mainly include variance in ation factor (VIF) and tolerance (TOL) (Sahani and Ghosh, 2021).…”