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Assessing the effects of air temperature and rainfall on malaria incidence: an epidemiological study across Rwanda and Uganda
6551PDF: 2393Appendix: 646HTML: 3347Appendix: 263 -
A dynamic, climate-driven model of Rift Valley fever
4888PDF: 2105Appendix: 591HTML: 1597 -
COVID-19, air quality and space monitoring
2031PDF: 636HTML: 23 -
Spatial inequalities in cancer with special reference to lung cancer across Europe and their implications for environmental health policy
639PDF: 250Supplementary materials: 32HTML: 10 -
Geographical accessibility to healthcare by point-of–interest data from online maps: a comparative study
1773PDF: 588Supplementary Materials: 164HTML: 34 -
Bayesian modelling of dengue incidence with climatic drivers: comparing fixed-effects, nonlinear and dynamic approaches
650PDF: 344Supplementary materials: 51HTML: 13 -
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Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases
2523PDF: 684Supplementary Materials: 401HTML: 221 -
Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa
4373PDF: 1932APPENDIX 1: 466APPENDIX 2: 496HTML: 1650 -
Predicting malaria cases using remotely sensed environmental variables in Nkomazi, South Africa
3187PDF: 1669APPENDIX: 505HTML: 313 -
Prediction of dengue cases using the attention-based long short-term memory (LSTM) approach
3103PDF: 1302Supplementary Materials: 201HTML: 130 -
Flexible scan statistic with a restricted likelihood ratio for optimized COVID-19 surveillance
980PDF: 317Supplementary Materials: 144HTML: 29 -
Report-back for geo-referenced environmental data: A case study on personal monitoring of temperature in outdoor workers
2622PDF: 1199APPENDIX: 395HTML: 87 -
Sandwich mapping of schistosomiasis risk in Anhui Province, China
3237PDF: 1263HTML: 1087 -
Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases
2528PDF: 877Supplementary materials: 217HTML: 116 -
Estimating malaria burden in Nigeria: a geostatistical modelling approach
7814PDF: 3226HTML: 3286
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