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Inference is bliss: Simulation for power estimation for an observational study of a cholera outbreak intervention.
Ratnayake, Ruwan; Checchi, Francesco; Jarvis, Christopher I; Edmunds, W John; Finger, Flavio.
  • Ratnayake R; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Checchi F; Centre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Jarvis CI; Epicentre, Paris, France.
  • Edmunds WJ; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
  • Finger F; Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom.
PLoS Negl Trop Dis ; 16(2): e0010163, 2022 02.
Article in English | MEDLINE | ID: covidwho-1745362
ABSTRACT

BACKGROUND:

The evaluation of ring vaccination and other outbreak-containment interventions during severe and rapidly-evolving epidemics presents a challenge for the choice of a feasible study design, and subsequently, for the estimation of statistical power. To support a future evaluation of a case-area targeted intervention against cholera, we have proposed a prospective observational study design to estimate the association between the strength of implementation of this intervention across several small outbreaks (occurring within geographically delineated clusters around primary and secondary cases named 'rings') and its effectiveness (defined as a reduction in cholera incidence). We describe here a strategy combining mathematical modelling and simulation to estimate power for a prospective observational study. METHODOLOGY AND PRINCIPAL

FINDINGS:

The strategy combines stochastic modelling of transmission and the direct and indirect effects of the intervention in a set of rings, with a simulation of the study analysis on the model results. We found that targeting 80 to 100 rings was required to achieve power ≥80%, using a basic reproduction number of 2.0 and a dispersion coefficient of 1.0-1.5.

CONCLUSIONS:

This power estimation strategy is feasible to implement for observational study designs which aim to evaluate outbreak containment for other pathogens in geographically or socially defined rings.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Simulation / Cholera Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: PLoS Negl Trop Dis Journal subject: Tropical Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pntd.0010163

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Computer Simulation / Cholera Type of study: Cohort study / Experimental Studies / Observational study / Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: PLoS Negl Trop Dis Journal subject: Tropical Medicine Year: 2022 Document Type: Article Affiliation country: Journal.pntd.0010163