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      Synergies between environmental degradation and climate variation on malaria re-emergence in southern Venezuela: a spatiotemporal modelling study

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          Summary

          Background

          Environmental degradation facilitates the emergence of vector-borne diseases, such as malaria, through changes in the ecological landscape that increase human–vector contacts and that expand vector habitats. However, the modifying effects of environmental degradation on climate–disease relationships have not been well explored. Here, we investigate the rapid re-emergence of malaria in a transmission hotspot in southern Venezuela and explore the synergistic effects of environmental degradation, specifically gold-mining activity, and climate variation.

          Methods

          In this spatiotemporal modelling study of the 46 parishes of the state of Bolívar, southeast Venezuela, we used data from the Venezuelan Ministry of Health including population data and monthly cases of Plasmodium falciparum malaria and Plasmodium vivax malaria between 1996 and 2016. We estimated mean precipitation and temperature using the ERA5-Land dataset and used monthly anomalies in sea-surface temperature as an indicator of El Niño events between 1996 and 2016. The location of suspected mining sites in Bolívar in 2009, 2017, and 2018 were sourced from the Amazon Geo-Referenced Socio-Environmental Information Network. We estimated measures of cumulative forest loss and urban development by km 2 using annual land cover maps from the European Space Agency Climate Change Initiative between 1996 and 2016. We modelled monthly cases of P falciparum and P vivax malaria using a Bayesian hierarchical mixed model framework. We quantified the variation explained by mining activity before exploring the modifying effects of environmental degradation on climate–malaria relationships.

          Findings

          We observed a 27% reduction in the additional unexplained spatial variation in incidence of P falciparum malaria and a 23% reduction in P vivax malaria when mining was included in our models. The effect of temperature on malaria was greater in high mining areas than low mining areas, and the P falciparum malaria effect size at temperatures of 26·5°C (2·4 cases per 1000 people [95% CI 1·78–3·06]) was twice as high as the effect in low mining areas (1 case per 1000 people [0·68–1·49]).

          Interpretation

          We show that mining activity in southern Venezuela is associated with hotspots of malaria transmission. Increased temperatures exacerbated malaria transmission in mining areas, highlighting the need to consider how environmental degradation modulates climate effect on disease risk, which is especially important in areas subjected to rapidly rising temperatures and land-use change globally. Our findings have implications for the progress towards malaria elimination in the Latin American region. Our findings are also important for effectively targeting timely treatment programmes and vector-control activities in mining areas with high rates of malaria transmission.

          Funding

          Biotechnology and Biological Sciences Research Council, Royal Society, US National Institutes of Health, and Global Challenges Research Fund.

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            Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations

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              Bayesian image restoration, with two applications in spatial statistics

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                Author and article information

                Contributors
                Journal
                101704339
                46425
                Lancet Planet Health
                Lancet Planet Health
                The Lancet. Planetary health
                2542-5196
                2 June 2023
                September 2022
                01 September 2023
                : 6
                : 9
                : e739-e748
                Affiliations
                Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK
                Instituto de Zoología y Ecología Tropical, Facultad de Ciencias, Universidad Central de Venezuela, Caracas, Venezuela
                Centro de Investigaciones Francesco Vitanza, Servicio Autónomo Instituto de Altos Estudios Dr Arnoldo Gabaldon, Ministerio del Poder Popular para la Salud, Bolívar, Venezuela
                Department of Infection Biology, London School of Hygiene & Tropical Medicine, London, UK
                Instituto de Zoología y Ecología Tropical, Facultad de Ciencias, Universidad Central de Venezuela, Caracas, Venezuela
                Centre for Biodiversity and Environment Research, University College London, London, UK
                Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK; Centre on Climate Change and Planetary Health, London School of Hygiene & Tropical Medicine, London, UK; Barcelona Supercomputing Center, Barcelona, Spain; Catalan Institution for Research and Advanced Studies, Barcelona, Spain
                Author notes
                Correspondence to: Dr Isabel Fletcher, Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London WC1E 7HT, UK isabel.fletcher@ 123456lshtm.ac.uk

                Contributors

                IKF and RL conceived the study. IKF collated the data, fitted the models, analysed the results, and wrote the manuscript. MEG helped conceive the study and provided interpretation and discussion of study results. JH-V and JEM provided the malaria case data. KEJ and CD provided input on model formulation and discussion of results. RL reviewed and revised the manuscript. All authors approved the final version of the manuscript, had full access to all the data in the study, and had final responsibility for the decision to submit for publication.

                Article
                NIHMS1902390
                10.1016/S2542-5196(22)00192-9
                10265648
                36087604
                1b271c7b-6e60-4cf4-8821-0aa94bcc98cc

                This is an Open Access article under the CC BY 4.0 license.

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