Identifying key factors in predicting Chikungunya and Zika transmission in French Polynesia: a data-driven mathematical model

Background Chikungunya and Zika are both arboviruses transmitted through the Aedes mosquitoes, which are ectothermic, leading to seasonal outbreak patterns of virus infections in the human population. Mathematical models linked with mosquito trap data, human case data, or both, have proven to be powerful tools for understanding the transmission dynamics of arboviral diseases. However, while predictive models should consider a variety of features in the environment, vectors, and hosts, it is not clear which aspects are essential to assist with short-term forecasting. Methodology We consider four simple models with various assumptions, including mosquito dynamics, temperature impacts, or both, and apply each model to forecast the Chikungunya and Zika outbreaks of nine different regions in French Polynesia. We use standard statistical criteria to compare the accuracy of each model in predicting the magnitude of the outbreak to select the most appropriate model to use as an alert system for arbovirus infections. Moreover, by calibrating our best model, we estimate biologically meaningful parameter values to explore the commonality and difference between Chikungunya and Zika epidemics. Conclusions We show that incorporating the mosquito population dynamics in the arbovirus transmission model is essential for accurate arbovirus case prediction. In addition, such enhancement in the accuracy of prediction is more obvious for the Chikungunya data than the Zika data, suggesting that mosquito dynamics play a more important role in Chikungunya transmission than Zika transmission. In contrast, incorporating the effects of temperature may not be necessary for past outbreaks in French Polynesia. With the well-calibrated model, we observe that the Chikungunya virus has similar but slightly higher transmissibility than the Zika virus in most regions. The best-fit parameters for the mosquito model suggest that Chikungunya has a relatively longer mosquito infectious period and a higher mosquito-to-human transmission rate. Further, our findings suggest that universal vector control plans will help prevent future Zika outbreaks. In contrast, targeted control plans focusing on specific mosquito species could benefit the prevention of Chikungunya outbreaks. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported in part by National Science Foundation grant DMS-2052109 to PJT, grants DMS-1853622 and DMS-2052648 to XH. PJT acknowledges research support from the Oberlin College Department of Mathematics. QH acknowledges research support from the College of Wooster. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The data for this study was openly available before the initiation of this study. The data was posted along with the paper titled "A comparative analysis of Chikungunya and Zika transmission." To download the data, follow the link https://www.sciencedirect.com/science/article/pii/S1755436517300014#sec0095 and check the section "Appendix A. Supplementary data." I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors.