key: cord-1022493-84u68mtk authors: Zhuang, Zian; Zhao, Shi; Lin, Qianying; Cao, Peihua; Lou, Yijun; Yang, Lin; He, Daihai title: Preliminary estimation of the novel coronavirus disease (COVID-19) cases in Iran: A reply to Sharifi date: 2020-04-30 journal: International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases DOI: 10.1016/j.ijid.2020.04.073 sha: 672eeba8c5da0bcc94993a61a5f06dbf4bb3439a doc_id: 1022493 cord_uid: 84u68mtk nan To the editor The worldwide outbreak of the novel coronavirus (SARS-Cov-2) pneumonia remains a major public health concern. We thank Sharifi et al.'s comments to our recent study (1) . In that paper we adopted the similar method as Imai's (2) , which was used to estimate the number of COVID-19 cases in the early stages of the COVID-19 outbreak in Wuhan, Hubei, China. The model provided a rough range estimation about the epidemic size and has been recognized by peers as a valid method in the early stage of an epidemic (3) (4) (5) . The accumulated evidence coincides with early estimation in scales. The estimation of the total infected cases could be improved if more evidence is available. We had discussed alternative scenarios (1) including smaller catchment population (e.g., 75% of the population), shorter detection window (e.g. different generation interval), different load factors of planes. A lower estimation of total infected cases is possible under the scenario in which a smaller catchment population is linked to those airports. Nevertheless, there are no solid evidence which specific scenario would be the reality now. Thus, we listed results under all scenarios. It is a weak argument that international flight travelers have a more extensive local social network, as they might have a smaller local social network due to losing connections while living overseas. Some social studies may be helpful to determine which is more reasonable. The report from Statistical center of Iran (6) supports that over 25% of the whole population live in rural area. However, according to the same reference (6), population size of the age group 1-14 is around 4% larger in rural areas, compared to the urban areas. This situation is likely to be a factor in reducing the onset of infection symptoms among rural population, since most of COVID-19 patients were aged from 30 to 79 (87%) (7) . Rural areas may be less dense compared to urban areas which is likely to result in decreased average number of effective contacts. Also, it is likely that there are not as many tests available for the rural population. Hence, overall, lower prevalence of infection in rural areas does not strongly reject the assumption that flight passengers are distributed homogeneously among rural and urban population. If individuals are infected in other countries, then fly to Iran and finally arrive in a third country, they need to go through multiple temperature screenings without being noticed since many airports have implemented boarding temperature screening. Thus, the probability is low. Meanwhile, according to the WHO Situation Report, the likely places of exposure for these 5 cases are outside reporting country and outside China (8) (9) (10) . It was difficult for Chinese passengers to use Iran as the connection for their international flights since Iran suspended all flights to and from China on 31 January 2020 (11). In addition, Qom is a significant destination of pilgrimage. Given the epidemic situation in Qom at the early stage of outbreak, it is likely that some COVID-19 cases were exported to other counties and regions. Based on the current information (8) (9) (10) (11) (12) (13) (14) and research (15) , it is reasonable to presume these cases exported from Iran were infected in Iran. If more laboratory evidence provided that these cases are infected outside Iran, results will be change. An evaluation version of novaPDF was used to create this PDF file. Purchase a license to generate PDF files without this notice. We did not consider other international flight since other countries did not disclose the number of COVID-19 cases imported from Iran and it is unreasonable to assume this number to be 0. In our model, numbers of passengers are determined for each country separately. Inputting additional information from other countries and corresponding passengers to our model can improve the estimation accuracy and narrow the confidence interval. As for those countries sharing borders with Iran, we did not include them as we could not find population flow data on land and maritime travel between those countries and Iran. The model we used is a simple model with a few parameters. We have provided the assumption, parameter values (effective catchment population, detection window, listed in Table 2 ) and reference in the methods part. Basic reproductive number (R 0 ) and the date of the epidemic onset were not involved in the model. The use of news did not affect the setting of our parameters. We mentioned the news in order to explain the reason why we conduct such research. An early estimation of epidemic is aimed to raise the public and government awareness. It gives a rough estimate of the total cases. Before a large-scale serological study is available, we already tried to consider as many scenarios as possible to prevent the result from being misinterpreted. As for the factors (governments measures) mentioned by Sharifi et al., we agree that it is important and it should be considered carefully when researchers try to forecast future development of epidemic situation. We appreciate great efforts made by Iranians in fighting against the epidemic and we thank Sharifi et al.'s comments to our study. As we explained, our method and estimate are robust and in line with (15) , but we also agree with (15) on the estimate of couple thousands in a less likely scenario. Our estimates in Table 2 included cases of several thousands. Ethical Approval and Consent to participate Not applicable. All data used are from public domain. Not applicable. All data used are from public domain Availability of data and materials All data used are from public domain Preliminary estimation of the novel coronavirus disease (COVID-19) cases in Iran: A modelling analysis based on overseas cases and air travel data Estimating the potential total number of novel 2019-nCoV) cases in Wuhan City, China. Preprint published by the Imperial College London Early dynamics of transmission and control of COVID-19: a mathematical modelling study. The Lancet Infectious Diseases Risk Assessment of Novel Coronavirus COVID-19 Outbreaks Outside China SARS-CoV-2 Infection among Travelers Returning from Wuhan, China Population and Housing Censuses, Selected Findings of the 2016 National Population and Housing Census Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention Coronavirus disease 2019 (COVID-19) Situation Report -33 COVID-19) Situation Report -34 COVID-19) Situation Report -36 df?sfvrsn=2791b4e0_2. 11. Iran Suspends China Flights over Coronavirus Minister Hasan Announces First Coronavirus Case in Lebanon MOH Registers First Two Novel Coronavirus (COVID-2019) in Oman Iranian couple diagnosed with COVID-19 in UAE, taking number of cases to 13 Estimation of Coronavirus Disease 2019 (COVID-19) Burden and Potential for International Dissemination of Infection From Iran An evaluation version of novaPDF was used to create this PDF file. Purchase a license to generate PDF files without this notice An evaluation version of novaPDF was used to create this PDF file. Purchase a license to generate PDF files without this notice. All authors conceived and conducted the research and wrote the draft. All authors approved the submission.