A population model for the 2017/18 listeriosis outbreak in South Africa
We introduce a compartmental model of ordinary differential equations for the population dynamics of listeriosis, and we derive a model for analysing a listeriosis outbreak. The model explicitly accommodates neonatal infections. Similarly as is common in cholera modeling, we include a compartment to...
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| Veröffentlicht in: | PloS one 2020-03, Vol.15 (3), p.e0229901-e0229901 |
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| creator | Witbooi, Peter Joseph Africa, Charlene Christoffels, Alan Ahmed, Ibrahim Hussin Ibrahim |
| description | We introduce a compartmental model of ordinary differential equations for the population dynamics of listeriosis, and we derive a model for analysing a listeriosis outbreak. The model explicitly accommodates neonatal infections. Similarly as is common in cholera modeling, we include a compartment to represent the reservoir of bacteria. We also include a compartment to represent the incubation phase. For the 2017/18 listeriosis outbreak that happened in South Africa, we calculate the time pattern and intensity of the force of infection, and we determine numerical values for some of the parameters in the model. The model is calibrated using South African data, together with existing data in the open literature not necessarily from South Africa. We make projections on the future outlook of the epidemiology of the disease and the possibility of eradication. |
| doi_str_mv | 10.1371/journal.pone.0229901 |
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The model explicitly accommodates neonatal infections. Similarly as is common in cholera modeling, we include a compartment to represent the reservoir of bacteria. We also include a compartment to represent the incubation phase. For the 2017/18 listeriosis outbreak that happened in South Africa, we calculate the time pattern and intensity of the force of infection, and we determine numerical values for some of the parameters in the model. The model is calibrated using South African data, together with existing data in the open literature not necessarily from South Africa. We make projections on the future outlook of the epidemiology of the disease and the possibility of eradication.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0229901</identifier><identifier>PMID: 32163438</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Applied mathematics ; Bacteria ; Bioinformatics ; Biology and Life Sciences ; Cholera ; Differential equations ; Disease ; Diseases ; Epidemics ; Epidemiology ; Food contamination & poisoning ; Infection ; Infections ; Listeria ; Listeriosis ; Medicine and Health Sciences ; Meningitis ; Mortality ; Mothers ; Neonates ; Newborn babies ; Newborn infants ; Ordinary differential equations ; Outbreaks ; Pathogens ; People and places ; Physical Sciences ; Population ; Population biology ; Population dynamics ; Pregnancy ; Reservoirs (Water) ; Sepsis ; Time ; Waterborne diseases</subject><ispartof>PloS one, 2020-03, Vol.15 (3), p.e0229901-e0229901</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Witbooi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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The model explicitly accommodates neonatal infections. Similarly as is common in cholera modeling, we include a compartment to represent the reservoir of bacteria. We also include a compartment to represent the incubation phase. For the 2017/18 listeriosis outbreak that happened in South Africa, we calculate the time pattern and intensity of the force of infection, and we determine numerical values for some of the parameters in the model. The model is calibrated using South African data, together with existing data in the open literature not necessarily from South Africa. We make projections on the future outlook of the epidemiology of the disease and the possibility of eradication.</description><subject>Analysis</subject><subject>Applied mathematics</subject><subject>Bacteria</subject><subject>Bioinformatics</subject><subject>Biology and Life Sciences</subject><subject>Cholera</subject><subject>Differential equations</subject><subject>Disease</subject><subject>Diseases</subject><subject>Epidemics</subject><subject>Epidemiology</subject><subject>Food contamination & poisoning</subject><subject>Infection</subject><subject>Infections</subject><subject>Listeria</subject><subject>Listeriosis</subject><subject>Medicine and Health Sciences</subject><subject>Meningitis</subject><subject>Mortality</subject><subject>Mothers</subject><subject>Neonates</subject><subject>Newborn babies</subject><subject>Newborn infants</subject><subject>Ordinary differential equations</subject><subject>Outbreaks</subject><subject>Pathogens</subject><subject>People and 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| subjects | Analysis Applied mathematics Bacteria Bioinformatics Biology and Life Sciences Cholera Differential equations Disease Diseases Epidemics Epidemiology Food contamination & poisoning Infection Infections Listeria Listeriosis Medicine and Health Sciences Meningitis Mortality Mothers Neonates Newborn babies Newborn infants Ordinary differential equations Outbreaks Pathogens People and places Physical Sciences Population Population biology Population dynamics Pregnancy Reservoirs (Water) Sepsis Time Waterborne diseases |
| title | A population model for the 2017/18 listeriosis outbreak in South Africa |
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