Patterns of foot-and-mouth disease virus detection in environmental samples in an endemic setting

Sarah R Mielke; Sevidzem Lendzele; Amy H Delgado; Mamoudou Abdoulmoumini; Simon Dickmu; Rebecca Garabed

doi:10.3389/fvets.2023.1157538

Patterns of foot-and-mouth disease virus detection in environmental samples in an endemic setting

Front Vet Sci. 2023 Jun 16:10:1157538. doi: 10.3389/fvets.2023.1157538. eCollection 2023.

Authors

Sarah R Mielke^{1

2}, Sevidzem Lendzele³, Amy H Delgado², Mamoudou Abdoulmoumini⁴, Simon Dickmu^{5

6}, Rebecca Garabed¹

Affiliations

¹ Department of Veterinary Preventive Medicine, The Ohio State University College of Veterinary Medicine, Columbus, OH, United States.
² United States Department of Agriculture's Animal and Plant Health Inspection Service (APHIS), Fort Collins, CO, United States.
³ Transmissible Diseases Ecology Laboratory, Department of Environmental Health, Faculty of Technology and Health Management, Université Libreville Nord, Libreville, Gabon.
⁴ School of Veterinary Science and Medicine, University of Ngaoundéré, Ngaoundéré, Adamawa, Cameroon.
⁵ The National Veterinary Laboratory (LANAVET), Garoua North, Cameroon.
⁶ University of Bamenda, Bambili, Cameroon.

Abstract

Foot-and-Mouth Disease virus (FMDV) is endemic in several regions and is a virus that can persist in the environment dependent on pH, relative humidity (RH), temperature, and matrix (i.e., soil, water, or air). Our previously published analysis of available viral persistence data showed that persistence is likely affected by interactions between RH, temperature, and matrix. Understanding these relationships will aid efforts to eliminate FMD, which has significant impacts on economies and food security. In Cameroon, West Africa, the livestock system consists of mobile (transhumant), transboundary trade and sedentary herds. Studying this system can provide information about the patterns of environmental detection of FMDV RNA that may influence approaches to virus elimination on premises during an outbreak. To improve our understanding of these patterns, we collected samples from individuals, vehicles, and along cattle pathways at three sedentary herds beginning on day one of owner-reported outbreaks, ending by day 30, and tested for the presence of FMD viral RNA using rRT-PCR. Our analysis suggests that detection decreases in soil surface samples with increased distance from herd and time from the first report of disease. Whereas time but not distance decreases detection in air samples. Interaction of RH and temperature suggests increased detection at high temperatures (>24°C) and RH (>75%), providing us with new information about the patterns of FMD viral RNA detection in and around cattle herds that could help to inform targeted virus elimination strategies, such as location and application of disinfectants.

Keywords: Bayesian analysis; disease modeling; endemic FMD; environment; viral RNA detection.