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Assessing the effects of air temperature and rainfall on malaria incidence: an epidemiological study across Rwanda and Uganda
6673PDF: 2474Appendix: 666HTML: 3373Appendix: 281 -
A dynamic, climate-driven model of Rift Valley fever
5010PDF: 2199Appendix: 614HTML: 1602 -
COVID-19, air quality and space monitoring
2126PDF: 694HTML: 24 -
Geographical accessibility to healthcare by point-of–interest data from online maps: a comparative study
2109PDF: 651Supplementary Materials: 189HTML: 39 -
Spatial inequalities in cancer with special reference to lung cancer across Europe and their implications for environmental health policy
842PDF: 438Supplementary materials: 53HTML: 18 -
Bayesian modelling of dengue incidence with climatic drivers: comparing fixed-effects, nonlinear and dynamic approaches
797PDF: 497Supplementary materials: 79HTML: 19 -
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Integrating agent-based disease, mobility and wastewater models for the study of the spread of communicable diseases
2647PDF: 770Supplementary Materials: 420HTML: 224 -
Random forest variable selection in spatial malaria transmission modelling in Mpumalanga Province, South Africa
4550PDF: 2034APPENDIX 1: 490APPENDIX 2: 517HTML: 1654 -
Flexible scan statistic with a restricted likelihood ratio for optimized COVID-19 surveillance
1064PDF: 384Supplementary Materials: 167HTML: 32 -
Predicting malaria cases using remotely sensed environmental variables in Nkomazi, South Africa
3330PDF: 1740APPENDIX: 545HTML: 321 -
Prediction of dengue cases using the attention-based long short-term memory (LSTM) approach
3803PDF: 1629Supplementary Materials: 222HTML: 144 -
Report-back for geo-referenced environmental data: A case study on personal monitoring of temperature in outdoor workers
2674PDF: 1281APPENDIX: 423HTML: 94 -
Sandwich mapping of schistosomiasis risk in Anhui Province, China
3325PDF: 1325HTML: 1096 -
Moran’s I and Geary’s C: investigation of the effects of spatial weight matrices for assessing the distribution of infectious diseases
2714PDF: 966Supplementary materials: 241HTML: 122 -
Estimating malaria burden in Nigeria: a geostatistical modelling approach
7957PDF: 3332HTML: 3291
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