How floods may affect the spatial spread of respiratory pathogens: the case of Emilia-Romagna, Italy in May 2023

Abstract The negative impact of floods on public health has been increasing, as climate change makes these events more frequent and intense. Floods are known to cause direct injury and favor the spread of many waterborne and vector-borne pathogens. Their effect on the circulation of respiratory pathogens, like influenza and SARS-CoV-2, is, however, still unclear. In this study, we quantify this effect through the analysis of large-scale behavioral data coupled to mathematical models of epidemic spread. We focus on the devastating floods occurred in Italy in 2023 and measure how they impacted human contact patterns within and between communities. We find a substantial increase in contacts occurring 3 weeks after the floods, both among residents of the affected areas and between them and those living in distant, unaffected areas of Italy. Then, through mathematical simulations, we determine that these disrupted contact patterns can carry a circulating pathogen to previously unaffected geographic areas, as well as increasing infection counts across the country. Our findings may help set up protocols to use large-scale human contact data to contain epidemic outbreaks before, during and in the aftermath of floods. Competing Interest Statement The authors have declared no competing interest. Funding Statement This study was partially supported by: Horizon Europe grant SIESTA (101131957) to E.V. 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 colocation maps used are available at https://dataforgood.facebook.com/dfg/ tools/colocation-maps I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the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 Data Availability Meta Colocation Maps, used to analyze the contact patterns and to infer between- and within-community mixing for stochastic simulations can be requested at https://dataforgood.facebook.com/dfg/ tools/colocation-maps