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When and why direct transmission models can be used for environmentally persistent pathogens
- Source :
- PLoS Computational Biology
- Publication Year :
- 2021
- Publisher :
- Public Library of Science (PLoS), 2021.
-
Abstract
- Variants of the susceptible-infected-removed (SIR) model of Kermack & McKendrick (1927) enjoy wide application in epidemiology, offering simple yet powerful inferential and predictive tools in the study of diverse infectious diseases across human, animal and plant populations. Direct transmission models (DTM) are a subset of these that treat the processes of disease transmission as comprising a series of discrete instantaneous events. Infections transmitted indirectly by persistent environmental pathogens, however, are examples where a DTM description might fail and are perhaps better described by models that comprise explicit environmental transmission routes, so-called environmental transmission models (ETM). In this paper we discuss the stochastic susceptible-exposed-infected-removed (SEIR) DTM and susceptible-exposed-infected-removed-pathogen (SEIR-P) ETM and we show that the former is the timescale separation limit of the latter, with ETM host-disease dynamics increasingly resembling those of a DTM when the pathogen’s characteristic timescale is shortened, relative to that of the host population. Using graphical posterior predictive checks (GPPC), we investigate the validity of the SEIR model when fitted to simulated SEIR-P host infection and removal times. Such analyses demonstrate how, in many cases, the SEIR model is robust to departure from direct transmission. Finally, we present a case study of white spot disease (WSD) in penaeid shrimp with rates of environmental transmission and pathogen decay (SEIR-P model parameters) estimated using published results of experiments. Using SEIR and SEIR-P simulations of a hypothetical WSD outbreak management scenario, we demonstrate how relative shortening of the pathogen timescale comes about in practice. With atttempts to remove diseased shrimp from the population every 24h, we see SEIR and SEIR-P model outputs closely conincide. However, when removals are 6-hourly, the two models’ mean outputs diverge, with distinct predictions of outbreak size and duration.<br />Author summary Mathematical models of the spread and progression of communicable disease in populations are important tools in efforts to prevent and control outbreaks. A common class of disease models assume that infection is transmitted directly from infectious to susceptible individuals when they are in close proximity—so called direct transmission models. These are used widely and have proven invaluable as simplified descriptions of a wide array of infectious diseases in diverse populations. However, many pathogens spread through indirect, environmental routes of transmission, for example via contact with contaminated water sources in the case of cholera, or inhalation of infectious airborne droplets for respiratory infections, such as Covid-19. We show that direct transmission models work well for such pathogens with short environmental lifetimes and where hosts shed pathogens into the environment at high rates. This means that we do not require information about environmental pathogen levels to understand the behaviour of outbreaks caused by these pathogens. When shedding rates are also low, e.g., with macroparasitic infections, or when variable environmental factors play a role in transmissibility, then explicit modelling of both the pathogen and environmental transmission will provide a more accurate picture than a direct transmission approximation.
- Subjects :
- Endemic Diseases
Pulmonology
Epidemiology
Physiology
Computer science
White spot disease
Model parameters
Molting
Pathology and Laboratory Medicine
Disease Outbreaks
law.invention
Medical Conditions
law
Statistics
Medicine and Health Sciences
Limit (mathematics)
education.field_of_study
Ecology
Approximation Methods
Ingestion
Simulation and Modeling
Eukaryota
Crustaceans
Shrimp
Infectious Diseases
Transmission (mechanics)
Computational Theory and Mathematics
Modeling and Simulation
Physical Sciences
Pathogens
Monte Carlo Method
Disease transmission
Research Article
Arthropoda
Population
Environment
Research and Analysis Methods
Communicable Diseases
Models, Biological
Respiratory Disorders
Cellular and Molecular Neuroscience
Modelling and Simulation
Genetics
Animals
Humans
Computer Simulation
Epidemics
education
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Probability
Stochastic Processes
Organisms
Computational Biology
Biology and Life Sciences
Bayes Theorem
Models, Theoretical
Invertebrates
Respiratory Infections
Epidemiological Models
Physiological Processes
Zoology
Mathematics
Subjects
Details
- ISSN :
- 15537358
- Volume :
- 17
- Database :
- OpenAIRE
- Journal :
- PLOS Computational Biology
- Accession number :
- edsair.doi.dedup.....da222ce69246cb79fbd0849f0347cac1