key: cord-335115-g9h8y2on authors: Patrikar, S.; Kotwal, A.; Bhatti, V.; Banerjee, A.; Chatterjee, K.; Kunte, R.; Tambe, M. title: Incubation Period and Reproduction Number for novel coronavirus (COVID-19) infections in India date: 2020-06-29 journal: nan DOI: 10.1101/2020.06.27.20141424 sha: doc_id: 335115 cord_uid: g9h8y2on Novel coronavirus (COVID 19) rapidly spread from China to other parts of the world. Knowledge of incubation period and reproduction number is important in controlling any epidemic. The distribution of these parameters helps estimate the epidemic size and transmission potential of the disease. We estimated incubation period and reproduction number of COVID 19 for India utilizing data reported by Ministry of Health and Family Welfare (MoHFW), Government of India (GOI) and data in public domain. The mean incubation period seems to be larger at 6.93 (SD=5.87, 95% CI: 6.11, 7.75). and 95th percentile estimate for best fit normal distribution is 17.8 days. Weibull distribution, the best fit for the reproduction number estimated pre lockdown reproduction number as 2.6 (95% CI=2.34, 2.86) and post lockdown reduced to 1.57 (95% CI=1.3 , 1.84) implying effectiveness of the epidemic response strategies. The herd immunity is estimated between 36 to 61% for R0 of 1.57 and 2.6 respectively. While the novel coronavirus (COVID-19) spread rapidly from China to other developed countries, India saw a steady flow of patients mod early March and by 10 May 2020, it had gripped the country with 63,420 confirmed cases and 2109 deaths [1] [2] . The novel coronavirus (SARS-CoV-2) though related is distinct from severe acute respiratory syndrome (SARS) coronavirus and Middle East respiratory syndrome (MERS) coronavirus 3 . Many researchers struggled to estimate the magnitude of the epidemic wherein the epidemiological parameters remained uncertain. Knowledge of key epidemiological parameters including incubation period and reproduction number is important in controlling any epidemic. The distribution of these parameters helps estimate the epidemic size and transmission potential 3-7 of the disease. The incubation period is defined as the time from infection to the onset of illness 8 and is crucial for epidemiological modelling in predicting the transmission dynamics, infectiousness and quarantine period 9 . It is also important for several important public health activities like length of active monitoring, surveillance and control. The reproduction number (R 0 ) is the most fundamental parameter in infectious disease dynamics describing the contagiousness or transmissibility of infectious agents and is defined as the average number of secondary cases caused by a single infectious individual in a entirely susceptible population 10 . An outbreak is expected to continue if R 0 has a value >1 and to end if R 0 is <1. R 0 fluctuates if the rate of human-to-human or human and vector interactions varies over time or space. There exists scant evidence which supports the applicability of R 0 outside the region for which the value was calculated 11 . Estimation of changes in transmission over time can provide insights into the epidemiological situation and identify whether outbreak control measures are adequate and are having the desired measurable effect, and help in undertaking midcourse corrections. Herd immunity is defined as the resistance to the spread of a contagious disease within a population that results if a sufficiently high proportion of individuals are immune to the disease, especially through vaccination or immunity post natural infection 12 . When a high proportion of the population is immune, it is difficult for All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 29, 2020. . https://doi.org/10.1101/2020.06.27.20141424 doi: medRxiv preprint infectious diseases to spread, because there are not many people who can be infected and the transmission chain gets broken. Our current understanding of these epidemiological parameters for India is limited. Hence this study was undertaken to address above issue and estimate incubation period and reproduction number of COVID-19 for India utilizing data reported by Ministry of Health and Family Welfare (MoHFW), Government of India (GOI) and the data available in public domain. The analysis is based on publicly available data. Data were retrieved from the official website of the MoHFW, GOI 1 16 . Since the analysis is based on publicly available data ethics approval was not required. The incubation period data post adjustment of delay-time in test results was subjected to best fit model. Besides normal distribution four other commonly used incubation period distribution (Weibull, Log normal, Gamma and Erlang) were fitted. Estimation of the median incubation period, mean (sd), and quantiles (5 th , 25 th , 75 th , 95 th and 97 th ) was also done. For reproduction number, the best fit model (Weibull distribution) was used. Besides the best, fit three more distributions based on review of literature for distribution of reproduction number (lognormal, Gamma and Exponential) were considered. The values of R 0 were estimated for pre and post lockdown period to evaluate the impact All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 29, 2020. . https://doi.org/10.1101/2020.06.27.20141424 doi: medRxiv preprint of the epidemic control measures instituted by the Government of India. The herd immunity (HI) estimate was based on R 0 value 12 . (HI= (R 0 -1) or R 0 = 1 − 1/R 0 ) The statistical software used were IBM SPSS Statistics for Windows version 23.0 (SPSS Inc., Chicago, Ill., USA) and EASY-FIT, a software system for data fitting in dynamical systems. Data on 268 lab confirmed cases were extracted, the range of age was from 1.5 years to 89 years with a mean age of 36.45 years (SD=±17.27). Ratio of male to female was 1.5:1 with 60.3% males and 39.7% females. Using date of exposure and date of confirmation of disease status/illness onset, the estimates of incubation period were determined. Table 1 gives the incubation period estimates for various distributions. We fitted five distributions to the data: Normal, Weibull, Log normal, Gamma and Erlang. The normal distribution provided best fit for data with median and mean incubation period of 6.93 (SD=±5.87, 95% confidence interval CI: 6.11-7.75). The incubation period ranged from 1 to 19.26 days (5 th percentile to 97 th percentile) for this best fit. The Weibull distribution was the best next fit with mean incubation period to be higher than normal distribution with mean of 8.17 (SD=8.10). Figure 1 show cumulative distribution functions for best fit. The median incubation period for other distributions ranged 3.46 to 6.06. The probability and cumulative distribution functions for various distributions in order of best fit is provided in the supplementary. The reproduction number was estimated for days before lockdown and post lockdown to assess the impact of various control measures to include social distancing adopted by India. Weibull distribution was the best fit for the reproduction number followed by Log Normal and Gamma distribution. We estimated the initial reproduction number before lockdown by GOI to be 2.6 (95% CI=2.34 -2.86) and post lockdown the reproduction number reduced to 1.57 (95% CI=1.3 -1.84). The herd immunity is estimated in the range of 61-62%. Table 2 gives the descriptive statistics of reproduction number before and post lock down. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This data driven paper to the best of our knowledge presents the estimates of incubation period and reproduction number of COVID-19 in India for the first time. We characterised the distribution of incubation period and reproduction number for COVID-19 for India. We estimated that the incubation period follows the best fit of normal distribution with around 7 days ranging from 1 to 22 day with 95 th percentile of the distribution at 17.8 days. The incubation period seems to be longer for India as compared to 2 to 10 days by WHO 13 and 2-12 days by ECDC 17 Weibull distribution seems to be the best fit for reproduction number distribution in India. The reproduction number for India is estimated to be 2.6 in pre lock down phase and reduced to around 1.6 post lockdown phase with a herd immunity threshold of 61.5%. Though the value of R 0 has reduced from 2.6 in pre lock down period to 1.57 in post lock down period. i.e. 60.38% reduction it is still greater than 1. COVID-19 epidemic will increase as long as R 0 is greater than 1 and control efforts to bring R 0 below 1 needs to be implemented aggressively. A report based on the impact of the interventions across 11 European countries estimated a posterior mean of 0.97 [0.14-2.14] for Norway and 2.64 [1.40-4 .18] for Sweden, with an average of 1.43 across the 11 country posterior means, a 64% reduction compared to the pre-intervention values 23 . A study from Wuhan, Hubei All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (95% CI: 2·47-2·86). The wide range of R 0 from different studies indicates the challenges in estimating R 0 . Additionally, R 0 is dynamic in the sense that any factor having the potential to influence the contact rate, including population density, social distancing, and seasonality will ultimately affect R 0 . Our estimate of herd immunity threshold as 61% (with R 0 =2.6) is staggering as 826,873,494 people need to be infected to achieve herd immunity in India which may result in high death rate. Many countries have implemented aggressive lock downs however some countries like Sweden had a different approach to tackle COVID-19 by taking individual responsibility for social distancing and keeping society functioning with no official lock down by the Sweden government and still successful in keeping the reproduction number in control 26 . Long term lockdowns are not sustainable as its ill effects impacts many other health programmes. As per WHO 27 the weekly detection of new tuberculosis cases in India has gone down by nearly 75 per cent during the COVID-19 lockdown. The malaria modelling analysis by the Global Malaria Programme at WHO 28 and the HIV modelling study, convened by the WHO and UNAID 29 , predicts the collateral damage of COVID will be as devastating as pandemic, with millions succumbing to preventable, treatable illness and disease. However, in absence of vaccine and other uncertainties regarding the virus, herd immunity is debatable issue as a preventive measure and achieving herd immunity is likely to be a long-drawn process. Limitations of the study: The data on complete information for estimating incubation period as well reproduction number could be extracted for limited number of cases. Also, the time delay of test results, with varying turn around time among States, for estimating incubation period was averaged for India based on the public domain information and media reports. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. This study provides the estimates for key epidemiological charachteristics of COVID-19 in India. The mean incubation period seems to be larger at 6.93 and 95 th percentile estimate for best fit normal distribution to be 17.8 days. Best fit for reproduction number follows weibull distribution. Our estimates for pre lockdown reproduction number was 2.6. and post lockdown the reproduction number reduced to 1.57. This implies and shows that the epidemic response strategies adopted by India are effective. However the herd immunity is estimated in the range of 36-61% for R 0 of 1.57 and 2.6 respectively. All rights reserved. No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted June 29, 2020. . https://doi.org/10.1101/2020.06.27.20141424 doi: medRxiv preprint Home | Ministry of Health and Family Welfare | GOI A novel coronavirus from patients with pneumonia in China Report 2: Estimating the potential total number of novel Coronavirus cases in Wuhan City Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study The Extent of Transmission of Novel Coronavirus in Wuhan, China, 2020 The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application WHO Coronavirus disease (COVID-19) Pandemic Centers of Disease Control and prevention Novel Coronavirus (2019-nCoV) Situation Report-7 -World Health Organization (WHO) Stockholm: ECDC; 2020 Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: a statistical analysis of publicly available case data No reuse allowed without permission. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint this version posted The Incubation Period of Coronavirus Disease 2019 (COVID-19) From Publicly Reported Confirmed Cases: Estimation and Application Report 13 -Estimating the number of infections and the impact of non-pharmaceutical interventions on COVID-19 in 11 European countries, Imperial College COVID-19 Response Team Estimation of the reproductive number of novel coronavirus (COVID-19) and the probable outbreak size on the Diamond Princess cruise ship: A data-driven analysis Real-time modeling and projections of the COVID-19 Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study Johns Hopkins University and USAID.The Potential Impact Of The Covid-19 Response On Tuberculosis In High-Burden Countries:A Modelling Analysis Global Malaria Programme All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted June 29, 2020. . https://doi.org/10.1101/2020.06.27.20141424 doi: medRxiv preprint All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted June 29, 2020. . https://doi.org/10.1101/2020.06.27.20141424 doi: medRxiv preprint Figure 1 : Cumulative distribution function for best fit Normal distribution for Incubation period for India All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted June 29, 2020. . https://doi.org/10.1101/2020.06.27.20141424 doi: medRxiv preprint All rights reserved. No reuse allowed without permission.(which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint this version posted June 29, 2020. . https://doi.org/10.1101/2020.06.27.20141424 doi: medRxiv preprint