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Studying the trend of the novel coronavirus series in Mauritius and its implications

Naushad Mamode Khan1, Ashwinee Devi Soobhug2, Maleika Heenaye-Mamode Khan3

  • 1Department of Economics and Statistics/Faculty of Social Sciences and Humanities, University of Mauritius, Réduit, Mauritius.

Plos One
|July 11, 2020
PubMed

Insights

Mauritius successfully controlled COVID-19 using public health interventions. This study developed a time series model to predict new cases, identifying significant factors like sanitary curfew and sensitization campaigns.

Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • The COVID-19 pandemic presented unprecedented global health challenges.
  • Mauritius achieved significant control over the novel coronavirus 2019 (COVID-19) pandemic.
  • The World Health Organization (WHO) urged in-depth research into COVID-19 evolution and treatment.

Purpose of the Study:

  • To propose an integer-valued time series model for analyzing COVID-19 case data in Mauritius.
  • To identify significant covariates influencing COVID-19 transmission in Mauritius.
  • To forecast future COVID-19 case numbers in Mauritius.

Main Methods:

  • Development and application of an integer-valued time series model with covariate specification.
  • Testing the significance of variables including sanitary curfew, sanitization campaigns, time, safe shopping guidelines, and climatic conditions.
  • Utilizing COM-Poisson mixture models for case prediction and analysis of over-dispersion and serial auto-correlation.

Main Results:

  • Sanitary curfew, sanitization campaigns, time, and safe shopping guidelines were identified as significant predictors of COVID-19 cases.
  • Climatic conditions were not found to be a significant factor.
  • Statistically significant over-dispersion estimates and serial auto-correlation parameters were observed, indicating unobservable effects.

Conclusions:

  • The proposed COM-Poisson mixture models accurately predicted COVID-19 cases in Mauritius with satisfactory mean squared errors.
  • Unobservable factors, such as pathological genesis and environmental influences, contribute to rapid zoonotic virus propagation.
  • Findings support policymakers in reinforcing health care systems and sanitary obligations to maintain pandemic control.

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