key: cord-0947052-qx0mpjwx authors: Yuan yuan, Cheng title: Statistical methods for batch screening of input populations by stage and group in COVID-19 nucleic acid testing date: 2020-04-07 journal: nan DOI: 10.1101/2020.04.02.20050914 sha: 48235c14a438639ab49f811cdc163a92122ece3f doc_id: 947052 cord_uid: qx0mpjwx Abstract Purpose: To screen for COVID-19 patients in immigration using minimal nucleic acid testing (NAT). Methods: In the first phase, nasopharyngeal swab samples from the inbound population were numbered and grouped. The samples in the group were mixed together, and a NAT test was performed. When the test result is negative, it means that everyone in the group is not infected and the screening of the group is complete. When the test results were positive, the group moved on to the second stage. In the second stage, all samples in the positive group will be tested individually for NAT. Results: The advantages and considerations of the method are discussed. Prevalence in the incoming population was a determinant of the sample size within the group. The lower the incidence, the larger the sample size within the group, the higher the savings in NAT and testing costs. Conclusion: This method has significant efficiency and cost advantages in COVID-19 screening. It can also be used to screen other populations, such as community populations and people at high risk of infection, etc. Key words: COVID-19; NAT; nucleic acid testing; screening; nasopharyngeal swab . CC-BY-NC-ND 4.0 International license It is made available under a 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 April 7, 2020. 15 March 2020 [2] , and 44 newly confirmed cases were found out from the entrying population [3] [4] [5] [6] [7] . Starting from 19 March 2020, the cities such as Shenzhen, Guangzhou, Shanghai and Beijing have successively performed the policy which nucleic acid testing (NAT) covers the whole entrying population from abroad [8] [9] [10] [11] . The formula equation used is the following: R software (Version 3.6.3) code to calculate y is the following: 1 p<-#input value of Incidence Rate 2 x<-c(2:(1/p)) where p is the incidence of entrying population, d is the number of confirmed cases of entrying population, t is the number of entrying population in the same period, q is the number of entrying population which bring one COVID-19 patient, y is the number of NAT, x is the number of sample each group, ymin is the minimum number of the NAT. According to formulas (1), when d = 44, t = 60,000, then p = 0.7333(1/10,000), and q = 13637. The incidence of entrying population is 0.7333 (1 / 10,000). On average, there is 13637 entrying persons which bring one COVID-19 patient. In order to find out this patient, 13637 entrying persons must be performed COVID-19 fluorescent RT-PCR testing, 13637 NAT are required. At the cost of RMB 160 per testing, the cost of 13637 NAT . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted April 7, 2020. . CC-BY-NC-ND 4.0 International license It is made available under a 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 April 7, 2020. This method is not only limited to entrying population detection, but also can be used in community poplation detection and close contact population detection [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] [26] [27] [28] . It should be noted that p is the determining factor for the number of persons in each group. To find out the patients, the lower the p, the greater the value of x and the greater the value of q-y ,and vice versa (Table 1, Figure 2, Figure 3 ). . CC-BY-NC-ND 4.0 International license It is made available under a 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 April 7, 2020. Figure 2 Scatter plot of incidence rate of entrying population and Percentage saved. It shows that the relationship between incidence rate and percentage saved, the lower incidence rate, the greater the percentage saved. . CC-BY-NC-ND 4.0 International license It is made available under a 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 April 7, 2020. It shows that the relationship between incidence rate and number of samples each group, the lower incidence rate, the greater the number of samples each group, more NAT can be saved. There are many factors that affect p, such as the international situation, country, city, observation period, customs policy, and characteristics of the entrying population. Sometimes it will cause large fluctuation of p. It is necessary to monitor p in time and adjust x in accordance with formula (2). When p fluctuates within a certain range, x should be adjusted according to the maximum value of p. [1] WHO Director-General's opening remarks at the media briefing on COVID-19 -11 March 2020. https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-atthe-media-briefing-on-covid-19---11-march-2020. [ . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted April 7, 2020. . https://doi.org/10.1101/2020.04.02.20050914 doi: medRxiv preprint Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases Relation Between Chest CT Findings and Clinical Conditions of Coronavirus Disease (COVID-19) Pneumonia: A Multicenter Study Chest CT for Typical 2019-nCoV Pneumonia: Relationship to Negative RT-PCR Testing Detection of 2019 novel coronavirus (2019-nCoV) by real-time RT-PCR Potential preanalytical and analytical vulnerabilities in the . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprint this version posted doi: medRxiv preprint 8 laboratory diagnosis of coronavirus disease 2019 (COVID-19) 2020;/j/cclm.ahead-of-print Diagnosing COVID-19: The Disease and Tools for Detection Covid-19 mass testing facilities could end the epidemic rapidly Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts [published correction appears in Lancet Glob Health Active Monitoring of Persons Exposed to Patients with Confirmed COVID-19 -United States A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version) Diagnosis and Treatment Plan for COVID-19 (Trial Version 6) International license It is made available under a 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 April 7, 2020. . https://doi.org/10.1101/2020.04.02.20050914 doi: medRxiv preprint