| 2 | Observed versus estimated actual trend of COVID-19 case numbers in Cameroon:A data-driven modelling显示文摘Controlling the COVID-19 outbreak remains a challenge for Cameroon,as it is for many other countries worldwide.The number of confirmed cases reported by health authorities in Cameroon is based on observational data,which is not nationally representative.The actual extent of the outbreak from the time when the first case was reported in the country to now remains unclear.This study aimed to estimate and model the actual trend in the number of COVID-19 new infections in Cameroon from March 05,2020 to May 31,2021 based on an observed disaggregated dataset.We used a large disaggregated dataset,and multilevel regression and poststratification model was applied prospectively for COVID-19 cases trend estimation in Cameroon from March 05,2020 to May 31,2021.Subsequently,seasonal autoregressive integrated moving average(SARIMA)modeling was used for forecasting purposes.Based on the prospective MRP modeling findings,a total of about 7450935(30%)of COVID-19 cases was estimated from March 05,2020 to May 31,2021 in Cameroon.Generally,the reported number of COVID-19 infection cases in Cameroon during this period underestimated the estimated actual number by about 94 times.The forecasting indicated a succession of two waves of the outbreak in the next two years following May 31,2021.If no action is taken,there could be many waves of the outbreak in the future.To avoid such situations which could be a threat to global health,public health Abbreviations:ACF,Autocorrelation Function;AIC,Akaike information criterion;COVID-19,Coronavirus Disease 2019;MAE,Mean Absolute Error;MAPE,Mean Absolute Percentage Error;MASE,Mean Absolute Scaled Error;ME,Mean Error;MPE,Mean Percentage Error;MRP,Multilevel Regression and Post-stratification;PACF,Partial Autocorrelation Function;PLACARD,Platform for Collecting,Analyzing and Reporting Data;SARIMA,Seasonal Autoregressive integrated moving average;SARS-CoV-2,Severe Acute Respiratory Syndrome Coronavirus 2. | Arsène Brunelle Sandie Mathurin Cyrille Tejiokem Cheikh Mbacké Faye Achta Hamadou Aristide Abah Abah Serge Sadeuh Mbah Paul Alain Tagnouokam-Ngoupo Richard Njouom Sara Eyangoh Ngu Karl Abanda Maryam Diarra Slimane Ben Miled Maurice Tchuente Jules Brice Tchatchueng-Mbougua | 2023 | Infectious Disease Modelling2023，8，1： | 0 |
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