向研究人员通报伊朗COVID-19流行病的流行病估计研究的方法和结果,我们的目标是进行快速审查。
我们搜索并收录了已发表的文章,预印手稿和报告,估计伊朗累计或每日死亡人数或COVID-19病例。我们发现了131项研究,其中包括29项。
纳入的研究提供了总共84个研究模型/情景组合的输出。16项研究使用3-4个室性疾病模型。疫情二月末(2020-04-19),预测的最低(和最高)值是1,777(388,951)的累计死亡,累计病例为20,588(2,310,161),在第四月末(2020-06-20),累计死亡人数为3,590(1,819,392),累计病例为144,305(4,266,964)。2020年最新日期的累计死亡人数(和病例)的最高估计为2020-12-19年的418,834人(2020-12-31年的41,475,792人)。模型估计预测了伊朗流行病的不祥进程。到2020年底,使用口罩的人口百分比从目前的情况增加到95%,可能会防止26,790例额外死亡(95%置信区间19,925-35,208)。
纳入研究中使用的疾病建模和统计方法报告的细节和程度差异很大。在预测结果的结果方面观察到更大的异质性。在流行病估计研究中考虑最低限度和首选报告项目可能会更好地为未来对可用模型和将要开发的新模型的修订提供信息。不考虑漏报会导致模型结果误导。
To inform researchers about the methodology and results of epidemic estimation studies performed for COVID-19 epidemic in Iran, we aimed to perform a rapid
review.
We searched for and included published articles, preprint manuscripts and reports that estimated numbers of cumulative or daily deaths or
cases of COVID-19 in Iran. We found 131 studies and included 29 of them.
The included studies provided outputs for a total of 84 study-model/scenario combinations. Sixteen studies used 3-4 compartmental disease models. At the end of month two of the epidemic (2020-04-19), the lowest (and highest) values of predictions were 1,777 (388,951) for cumulative deaths, 20,588 (2,310,161) for cumulative
cases, and at the end of month four (2020-06-20), were 3,590 (1,819,392) for cumulative deaths, and 144,305 (4,266,964) for cumulative
cases. Highest estimates of cumulative deaths (and
cases) for latest date available in 2020 were 418,834 on 2020-12-19 (and 41,475,792 on 2020-12-31). Model estimates predict an ominous course of epidemic progress in Iran. Increase in percent population using masks from the current situation to 95% might prevent 26,790 additional deaths (95% confidence interval 19,925-35,208) by the end of year 2020.
Meticulousness and degree of details reported for disease modeling and statistical methods used in the included studies varied widely. Greater heterogeneity was observed regarding the results of predicted outcomes. Consideration of minimum and preferred reporting items in epidemic estimation studies might better inform future revisions of the available models and new models to be developed. Not accounting for under-reporting drives the models\' results misleading.