TY - JOUR
T1 - Optimal sampling frequency and site selection for wastewater and environmental surveillance of infectious pathogens
T2 - A value of information assessment
AU - Impalli, Isabella
AU - Bergland, Erik
AU - Saad-Roy, Chadi M.
AU - Grenfell, Bryan T.
AU - Levin, Simon A.
AU - Larsson, D. G.Joakim
AU - Laxminarayan, Ramanan
N1 - Publisher Copyright:
© 2025 Impalli et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2025/6
Y1 - 2025/6
N2 - Wastewater and environmental surveillance (WES) is a promising method of detecting infectious diseases in human and animal populations and offers significant advantages over traditional surveillance methods in the early detection of outbreaks. However, WES involves financial and human resources, and public policy decisions must determine whether the benefits of WES outweigh the costs, particularly in low-resource areas. The selection of surveillance sites, sampling frequency, and test sensitivity and specificity are crucial determinants of WES effectiveness and cost-efficiency. We created an analytical model and numerical simulations of disease arrival, spread, and WES strategies to determine the optimal sampling frequency for two interacting patches, each represented by a different sampling site. We show that it is optimal to test in one patch more frequently than it is to test in both patches less frequently if the patches are sufficiently interactive, surveillance is of sufficient sensitivity and specificity, and setup costs are substantial. In our value of information (VOI) assessment, the net value of surveillance information for both patches is non-monotonic with respect to the degree of patch interaction. Increased mixing between the patches allows for quicker surveillance detection but is worse for overall infection burden. Overall, optimizing the value of surveillance information for all patches being surveilled requires coordination and deliberate selection of surveillance sites and sampling frequencies. This paper provides a VOI assessment of WES to determine the optimal number of sites and sampling frequency at a high level of abstraction, leaving opportunity to adapt the model to specific pathogens and populations as needed. Our findings can inform the cost-efficient implementation of WES for infectious diseases, particularly in resource-constrained settings.
AB - Wastewater and environmental surveillance (WES) is a promising method of detecting infectious diseases in human and animal populations and offers significant advantages over traditional surveillance methods in the early detection of outbreaks. However, WES involves financial and human resources, and public policy decisions must determine whether the benefits of WES outweigh the costs, particularly in low-resource areas. The selection of surveillance sites, sampling frequency, and test sensitivity and specificity are crucial determinants of WES effectiveness and cost-efficiency. We created an analytical model and numerical simulations of disease arrival, spread, and WES strategies to determine the optimal sampling frequency for two interacting patches, each represented by a different sampling site. We show that it is optimal to test in one patch more frequently than it is to test in both patches less frequently if the patches are sufficiently interactive, surveillance is of sufficient sensitivity and specificity, and setup costs are substantial. In our value of information (VOI) assessment, the net value of surveillance information for both patches is non-monotonic with respect to the degree of patch interaction. Increased mixing between the patches allows for quicker surveillance detection but is worse for overall infection burden. Overall, optimizing the value of surveillance information for all patches being surveilled requires coordination and deliberate selection of surveillance sites and sampling frequencies. This paper provides a VOI assessment of WES to determine the optimal number of sites and sampling frequency at a high level of abstraction, leaving opportunity to adapt the model to specific pathogens and populations as needed. Our findings can inform the cost-efficient implementation of WES for infectious diseases, particularly in resource-constrained settings.
UR - https://www.scopus.com/pages/publications/105009781922
UR - https://www.scopus.com/pages/publications/105009781922#tab=citedBy
U2 - 10.1371/journal.pcbi.1013190
DO - 10.1371/journal.pcbi.1013190
M3 - Article
C2 - 40561147
AN - SCOPUS:105009781922
SN - 1553-734X
VL - 21
JO - PLoS computational biology
JF - PLoS computational biology
IS - 6
M1 - e1013190
ER -