Modeling the Lassa fever outbreak synchronously occurring with cholera and Covid-19 outbreaks in Nigeria 2021
A threat to Global Health Security
Bibliographic Data
| ID | 19593746 |
|---|---|
| Authors | Nancy B Tahmo (0000-0003-2745-745X, University of Nebraska Medical Center, corresponding author), Frankline Sevidzem Wirsiy (0000-0001-5767-7344, Amref Health Africa, corresponding author), David Brett-Major (0000-0002-7583-8495, University of Nebraska Medical Center, corresponding author) |
| Editors | Saskia Popescu (0000-0002-1521-8139) |
| Year | 2023 |
| Volume | 3 |
| Issue | 5 |
| Pages | e0001814 |
| Publication date | 2023-05-16 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | PLOS Global Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2767-3375 • E-ISSN: 2767-3375 |
| Publisher | Public Library of Science (PLoS) (PUBLISHER) |
| DOI | 10.1371/journal.pgph.0001814 |
| PMID | 37192152 |
| OpenAlex | W4376871063 |
| Language | EN |
| References cited | 23 |
Nigeria struggles with seasonal outbreaks of Lassa fever (LF), with 70 to 100% of its states affected annually. Since 2018, the seasonal dynamics have changed with a stark increase in infections, though the pattern in 2021 differed from the other years. Nigeria had three outbreaks of Lassa Fever in 2021. In that year, Nigeria also experienced substantial burdens from COVID-19 and Cholera. There is potential that these three outbreak events interacted with each other. This may have been from community disruption and so changes in how people access the health system, how the health system responds, or overlapping biological interactions, misclassification, social factors, misinformation, and pre-existing disparities and vulnerabilities. We assessed the syndemic potential of Lassa Fever, COVID-19, and Cholera through modeling their interactions across the 2021 calendar year employing a Poisson regression model. We included the number of states affected and the month of the year. We used these predictors to forecast the progression of the outbreak using a Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The Poisson model prediction for the confirmed number of Lassa fever cases was significantly dependent on the number of confirmed COVID-19 cases, the number of states affected, and the month of the year (p-value
Autoregressive integrated moving average · Dengue fever · Disease · Environmental health · Geography · Lassa fever · Outbreak · Pandemic · Poisson regression · Statistics · Time series · COVID-19 epidemiological studies · Disaster Response and Management · Mathematics · Medicine · Viral Infections and Outbreaks Research · Internal Medicine · Virology
| Highly cited | No |
|---|