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Moving-average based index to evaluate the epidemic trend of COVID-19 outbreak
Yun-ting He; Hao He; Jing Zhai; Xiao-jin Wang; Bing-shun Wang.
Afiliação
  • Yun-ting He; School of Public Health, Shanghai Jiao Tong University School of Medicine
  • Hao He; School of Public Health, Shanghai Jiao Tong University School of Medicine
  • Jing Zhai; School of Public Health, Shanghai Jiao Tong University School of Medicine
  • Xiao-jin Wang; Department of Biostatistics, Clinical Research Institute, Shanghai Jiao Tong University School of Medicine
  • Bing-shun Wang; Department of Biostatistics, Clinical Research Institute, Shanghai Jiao Tong University School of Medicine
Preprint em En | PREPRINT-MEDRXIV | ID: ppmedrxiv-20027730
ABSTRACT
[ABSTRACT]A pneumonia outbreak caused by a novel coronavirus (COVID-19) occurred in Wuhan, China at the end of 2019 and then spread rapidly to the whole country. A total of 81,498 laboratory-confirmed cases, including 3,267 deaths (4.0%) had been reported in China by March 22, 2020, meanwhile, 210,644 laboratory-confirmed cases and 9,517 deaths (4.5%) were reported outside China. Common symptoms of COVID-19 pneumonia included fever, fatigue and dry cough. In face of such a sudden outbreak of emerging novel infectious diseases, we have no history to learn from and no evidence to count on. Traditional models often predict inconsistent results. There is an urgent need to establish a practical data-driven method to predict the evolutionary trend of the epidemic, track and prejudge the current epidemic situation after the COVID-19 outbreak. Here we propose a simple, directly and generally applicable index and we name it epidemic evaluation index (EEI), which is constructed by 7-day moving average of the log-transformed daily new cases (LMA). EEI could be used to support the decision-making process and epidemic prevention and control strategies through the evaluation of the current epidemic situation. First, we used SARS epidemic data from Hong Kong in 2003 to verify the practicability of the new index, which shows that the index is acceptable. The EEI was then applied to the COVID-19 epidemic situation analysis. We found that the trend direction of different districts in China changed on different date during the epidemic. At the national level and at local Hubei Province level, the epidemic both peaked on February 9. While the peak occurred relatively earlier, i.e. on February 5 in other provinces. It demonstrated the effectiveness of decisive action and implementations of control measures made by Chinese governments. While local governments should adjust management measures based on local epidemic situation. Although the epidemic has eased since late February, continued efforts in epidemic control are still required to prevent transmission of imported cases in China. However, the global COVID-19 epidemic outside China continues to expand as indicated by the EEI we proposed. Currently, efforts have been made worldwide to combat the novel coronavirus pandemic. People all over the world should work together and governments of all countries should take efficient measures in the light of Chinas experience and according to national circumstances and local conditions.
Licença
cc_by_nc_nd
Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-MEDRXIV Tipo de estudo: Experimental_studies / Observational_studies / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: 1 Coleções: 09-preprints Base de dados: PREPRINT-MEDRXIV Tipo de estudo: Experimental_studies / Observational_studies / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Preprint
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