Inferring person-to-person networks of Plasmodium falciparum transmission: is routine surveillance data up to the task?

Inference of person-to-person transmission networks using surveillance data is increasingly used to estimate spatiotemporal patterns of pathogen transmission. Several data types can be used to inform transmission network inferences, yet the sensitivity of those inferences to different data types is not routinely evaluated. We evaluated the influence of different combinations of spatial, temporal, and travel-history data on transmission network inferences for Plasmodium falciparum malaria. We found that these data types have limited utility for inferring transmission networks and may overestimate transmission. Only when outbreaks were temporally focal or travel histories were accurate was the algorithm able to accurately estimate the reproduction number under control, R c . Applying this approach to data from Eswatini indicated that inferences of R c and spatiotemporal patterns therein depend upon the choice of data types and assumptions about travel-history data. These results suggest that transmission network inferences made with routine malaria surveillance data should be interpreted with caution. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement JHH acknowledges support from a National Science Foundation Graduate Research Fellowship and a Richard and Peggy Notebaert Premier Fellowship. BG and TAP received support from a grant from the Bill and Melinda Gates Foundation (OPP 1132226 to BG). MSH received support from NIAID (AI101012). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ### 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: Ethical approval was obtained from the Eswatini Ministry of Health, the University of California, San Francisco, and the University of Notre Dame (IRB 19-06-5408). All data were analyzed anonymously. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. 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 and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The code and simulated data to reproduce the analyses can be found at https://github.com/johnhhuber/SpaceTime_Networks. The data collected from Eswatini contains sensitive household locations and are unable to be shared due to institutional review board restrictions.