Development of a computational model to inform environmental surveillance sampling plans for Salmonella enterica serovar Typhi in wastewater.
PLoS Negl Trop Dis
; 18(3): e0011468, 2024 Mar.
Article
em En
| MEDLINE
| ID: mdl-38551999
ABSTRACT
Typhoid fever-an acute febrile disease caused by infection with the bacterium Salmonella enterica serotype Typhi (S. Typhi)-continues to be a leading cause of global morbidity and mortality, particularly in developing countries with limited access to safe drinking water and adequate sanitation. Environmental surveillance, the process of detecting and enumerating disease-causing agents in wastewater, is a useful tool to monitor the circulation of typhoid fever in endemic regions. The design of environmental surveillance sampling plans and the interpretation of sampling results is complicated by a high degree of uncertainty and variability in factors that affect the final measured pathogens in wastewater samples, such as pathogen travel time through a wastewater network, pathogen dilution, decay and degradation, and laboratory processing methods. Computational models can, to an extent, assist in the design of sampling plans and aid in the evaluation of how different contributing factors affect sampling results. This study presents a computational model combining dynamic and probabilistic modeling techniques to estimate-on a spatial and temporal scale-the approximate probability of detecting S. Typhi within a wastewater system. This model may be utilized to inform environmental surveillance sampling plans and may provide useful insight into selecting appropriate sampling locations and times and interpreting results. A simulated applied modeling scenario is presented to demonstrate the model's functionality for aiding an environmental surveillance study in a typhoid-endemic community.
Texto completo:
1
Coleções:
01-internacional
Contexto em Saúde:
2_ODS3
/
3_ND
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4_TD
Base de dados:
MEDLINE
Assunto principal:
Salmonella
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Salmonella typhi
/
Febre Tifoide
Limite:
Humans
Idioma:
En
Revista:
PLoS Negl Trop Dis
Ano de publicação:
2024
Tipo de documento:
Article