Additional file 1 of The effects of urbanization, temperature, and rainfall on Aedes aegypti and Aedes albopictus mosquito abundance across a broad latitudinal gradient in Central Africa

Additional file 1: Text S1. Pathogen detection methods: RNA extraction and RT-PCR. Fig. S1. Humans observed at collection sites in Douala, Kribi, and Yaounde. Fig. S2. Relative humidity (in percent) and temperature (in degrees Celsius) measurements from each of the six cities. Fig. S3. Monthly rainfall and mosquito abundance (mosquitoes/3 h) for ten sites in Yaounde. Fig. S4. Monthly population growth rate of Ae. aegypti plotted against abundance of Ae. albopictus in the preceding month (A) and vice versa (B). Table S1. Previous studies on Ae. aegypti abundance and urbanization. Table S2. Previous studies on Ae. albopictus abundance and urbanization. Table S3: Sequence of primers used for viral detection. Table S4. Model comparison of different radii for urbanization index predicting the number of larval habitat containers. Table S5. Model comparison of different radii for urbanization index predicting the number of larval habitat containers with mosquito larvae. Table S6. Model comparison of different radii for urbanization index predicting the number of human hosts. Table S7. Model comparison of different radii for urbanization index predicting the number of animal hosts. Table S8. Model comparison of different radii for urbanization index predicting the abundance of Ae. aegypti mosquitoes. Table S9. Analysis of Ae. aegypti abundance in six cities with urbanization index (UI), with temperature, humidity, and the sampling month’s rain as predictors. Table S10. Analysis of Ae. aegypti abundance in five cities (all but Yaounde) with structures within 100 m, city, temperature, humidity, and sampling month’s rain as predictors. Table S11. Analysis of Ae. aegypti abundance with number of humans, temperature, humidity, and monthly rainfall as predictors. Table S12. Model comparison of different radii for urbanization index predicting the abundance of Ae. albopictus mosquitoes. Table S13. Analysis of Ae. albopictus abundance in the three cities where this species was found, with urbanization index (UI) interacting with city, and temperature, humidity, and prior month’s rain as predictors. Table S14. Analysis of Ae. albopictus abundance in the two cities where this species was found, and larval habitat studies were performed (Douala and Kribi), with larval containers, city, temperature, humidity, and prior month’s rain as predictors. Table S15. Analysis of Ae. albopictus abundance in the two cities where this species was found, and larval habitat studies were performed (Douala and Kribi), with larval containers with mosquito larvae (pos. containers), city, temperature, humidity, and prior month’s rain as predictors. Table S16. Analysis of Ae. albopictus abundance in the two cities where this species was found, and larval habitat studies were performed (Douala and Kribi), with larval containers with Ae. albopictus mosquito larvae (Alb. larvae), city, temperature, humidity, and prior month’s rain as predictors. Table S17. Analysis of Ae. albopictus abundance in the two cities where this species was found, and larval habitat studies were performed (Douala and Kribi), with the fraction of larval containers containing mosquito larvae (Cont. index), city, temperature, humidity, and prior month’s rain as predictors. Table S18. Analysis of Ae. albopictus abundance in the two cities where this species was found, and larval habitat studies were performed (Douala and Kribi), with Structures within 100 m, city, temperature, humidity, and prior month’s rain as predictors. Table S19. Analysis of Ae. albopictus abundance in the three cities where this species was found, with humans, city, temperature, humidity, and prior month’s rain as predictors. Table S20. Compiled minimum infection rates (MIR) for studies that detected Zika virus in field-caught specimens of Ae. aegypti and Ae. albopictus.