Spatial Point Pattern Analysis of Environmental Effects on Valley Fever Intensity in Phoenix, Arizona

ABSTRACT Using a novel Arizona Medicaid data set, we model Valley fever (VF) cases in the Phoenix Metropolitan Area as a spatial point process during six month intervals between 2013-2023. We estimate the intensity function of VF cases, observed at residential locations of patients, as a function of environmental covariates available at high spatial resolutions, including land cover type, change in land cover type, Normalized Difference Vegetation Index (NDVI), change in NDVI, and a Habitat Suitability Index (HSI) for the Coccidioides fungus. Models with all covariates included and quadratic terms for NDVI, NDVI difference, and HSI tend to perform the best. We show that land cover change and HSI measured at the residential (point) level are useful for understanding VF risk. Furthermore, we find that NDVI and its semesterly changes appear to have a nonlinear relationship with the intensity of VF cases. Despite more pronounced peaks in predicted intensities for our most complex model compared to our simplest model, we show that even our best, most complex model underestimates the intensity in portions of the study region. Thus, our results provide initial evidence that spatially localized environmental information is useful for examining VF incidence among Medicaid patients in the study area. Competing Interest Statement The authors have declared no competing interest. Funding Statement This work was supported under the National Institutes of Health, United States grant DMS-1615879. 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 Institutional Review Board of Arizona State University gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the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 Footnotes We Have changed the nature of the land cover change covariate which has not affected overall model results significantly but the interpretation is different and the model results (i.e. effect size and statistical significance) for this particular covariate are new. We have also added predicted intensity plots, accompanying discussion, and updated various small errors and typos. Data Availability The empirical patient data are restricted by a data-sharing agreement with the Arizona Health Care Cost Containment System and cannot be shared. We have created a simulated patient dataset that is available online as supplementary information to this study. Environmental datasets used in the study are available at https://github.com/jginos/VF-SPP-Analysis.