key: cord-0924573-iw3pmgaa authors: Wahid, A.; Khan, A.; Iqbal, Q.; Mohammad, N. title: The Epidemiology of COVID-19 and applying Non Pharmaceutical interventions by using the Susceptible, Infectious Recovered epidemiological Model in Pakistan. date: 2020-05-13 journal: nan DOI: 10.1101/2020.05.08.20095794 sha: 590818561ec37e9c23376503feab903836b6f774 doc_id: 924573 cord_uid: iw3pmgaa Introduction: The COVID-19 is caused by the virus known as sever acute respiratory syndrome corona virus 2 (SARS-CoV-2) having the common symptoms such as Flue, fever, dry cough and shortness of breath. The first case was reported in WUHAN city china in December 2019 and it spread to the whole world, WHO declared as world pandemic on 11th march 2020. SIR Epidemiological Model: The first case in Pakistan was confirmed on 26th Feb 2020 as by the 8th April 2020 the total no of confirmed cases 4187 with 58 deaths and 467 recoveries throughout the country. The upcoming situation of the COVID-19 in Pakistan is forecasted by using SIR epidemiological, which is one of the mathematical derivative models with great accuracy rate prediction used for infectious disease. This model was introduced in the early 20th century. Results: Pakistan is will be having a heavy burden of patients 80000 plus infected patients 45000 recoveries 10000 hospitalized 3000 ICU and 800 plus deaths in the next 20 days. A complete lock down, social distancing and imposing curfew to keep every person at home can save Pakistan from a very huge number 1000000 infected patients with huge number of causalities with next 2 months. Key words: COVID-19, Coronavirus COV2, Pakistan, SIR model The Coronaviruse disease 2019 (COVID-19) is caused by the virus known as sever acute respiratory syndrome corona virus 2 (SARS-CoV-2) having the common symptoms such as Flue, fever, dry cough and shortness of breath with complications to develop pneumonia and failure of the other vital organs which lead to death of the patient[1]. first case was identified in WUHAN city of Hubei province of China in December 2019 [2] . The dramatic spread of virus through the whole world was declared COVID-19 pandemic by WHO on 11 th of march 2020 [3] . More than 1363123 cases of COVID-19 have been reported in 209 countries and territories, resulting in approximately 76383 deaths. More than 293833 people have since recovered by 8 th April 2020[4]. The first case in Pakistan was confirmed on 26 th Feb 2020 as by the 8 th April 2020 the total no of confirmed cases 4187 with 58 deaths and 467 recoveries throughout the country [5] . Comparatively Pakistan with other countries such as UK, Iran, Italy, USA, Spain, Germany and other European countries, the no of positive patients of Pakistan are not as rapidly increasing as the no of patients of the other countries. The early positive cases in Pakistan were received from the neighbor country Iran through the Toftan border thousands of persons (Zaireen) travel to Iran on monthly bases for their religious pilgrims (Ziarat) to the different cities of Iran [5] . The government of Pakistan didn't allow the Zaireens to the local societies and kept them in Quarantines for 14 days with performing their COVID19 tests. All the schools Educational institutes were early closed for unknown period of time, the other markets, hotels and other crowded and rushed places were imposed a lock down for 20 days which may be extended for unknown period. 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 May 13, 2020. . https://doi.org/10.1101/2020.05.08.20095794 doi: medRxiv preprint Pakistan is in the early stage of the COVID-19 pandemic. So it is very important to predict the COVID19 by using mathematical epidemiological models to predict the upcoming situation of the COVID-19 in Pakistan. The SIR epidemiological is one of the mathematical derivative models with great accuracy rate prediction used for infectious disease. This model was introduced in the early 20 th century by the scientist Kermack and McKendrick in 1927[6] . This model consist three compartments, The whole population is placed in these three compartments by having same characteristics in same compartment. The patient infected will be removed from S compartment to I compartment and the patient who recover or die will be move from I compartment to R compartment. [7] This Mathematical Model has three compartments which are Susceptible (S), Infectious (I) and Recovered (R). The population of each compartment has its own characteristics the population of susceptible will remain susceptible unless comes in contact with infectious population and get infected will leave susceptible compartment and enter the infectious compartment and the infected population who recover or die will be removed from infectious compartment to recovered compartment. 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. Contact Rate: • The number of the susceptible people an infectious person contacts. Physical contact (Skin to skin contact) Non-physical contact (two-way conversation of 3+words in physical presence) • Reflex mixing of the population. • The probability that a contact between a susceptible person and infected person results in infection. • The period of time that infected person can pass the infection. • The inverse of the removal rate • The number of secondary cases resulting from one case in 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 May 13, 2020. (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 May 13, 2020. Figure 1A , Figure 1B) The demographic of COVID-19 positive patients in Pakistan are almost of all age categories both male and female as shown figure1C. [5] (Fig. 1A,1B,1C Here ) The whole population (220000000) of Pakistan is susceptible to COVID-19 infection, which was brought by very less number of people to the country. As this infection is going to spread the infectious period of the disease will start, so the number of infected will rise along with recovered cases. 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 May 13, 2020. . https://doi.org/10.1101/2020.05.08.20095794 doi: medRxiv preprint The rate at which susceptible population will become infected population depends on different factors: [10] At what speed the disease is going to spread naturally (unique to the virus) Contact rate of the population (unique to the society) How many tests performed for Detection? (unique to medical infra structure) These are the factors which are responsible to the rate at which the susceptible population is going to be infectious population, and this parameter is known as β . The Rate at which the people are going to recover is mostly related the pharmacological treatment and the unique to the virus, and this parameter is known as γ in the model. [11] The figure 2A . This model predicts that 50 million people will be infected in the upcoming four months if no proper measures are taken. These four months are going to be very challenging for Pakistan the state has to take every possible opportunity to combat the situation. The number of hospitalize patients are going to increase rapidly with increased fatality rate. Figure 2A Here 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 May 13, 2020. . https://doi.org/10.1101/2020.05.08.20095794 doi: medRxiv preprint The actual cases which are confirmed by the government of Pakistan are from 26 th Feb 2020 as by the 8 th April 2020 the total infected cases 4187 with 58 deaths and 467 recoveries throughout the country [9] . The whole population is susceptible and according the present contact rate and transmissibility controlled by the government the predicted cases by the end of this month 30 th April 2020 the no of infected cases are going to reach 80000 plus with 800 plus deaths, 10000 plus hospitalized, 3000 plus ICU and 45000 plus recoveries as shown in the figure 2B . The no of the patient may increase or decrease which depends on contact rate and transmissibility. Figure 2B Here The health care system of Pakistan is not well equipped and developed to handle this large number of patients who will be hospitalized which will result in the collapse of the healthcare system in Pakistan [12] and the other emergencies and chronic disease may cause many deaths. To decrease these large numbers, the government should play its role through non-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 May 13, 2020. . https://doi.org/10.1101/2020.05.08.20095794 doi: medRxiv preprint pharmacological interventions [13] . These interventions are decreasing the contact rate by isolation, quarantine, lock down or any other means that reduce the transmissibility rate which will reduce the number COVID-19 positive cases. Figure 2C and Figure 2D Here) • The SIR Model is closed system model the population of every compartment has its own characteristics. 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. • We have assumed equal susceptibility to COVID-19, of all ages, gender and the having the co-morbidities • The number of tests performed in Pakistan is very low as compare to the other countries so our absolute positive number might be low so we have assumed that increase the number of test will increase the number of absolute cases. • The SIR Model will Allow for easy modeling of epidemic • This model can easily predict the no of infected, recovered, hospitalized, ICU and death for a period of time which can prepare the state for epidemics. • This model can predict for both longer and shorter period of times • Non Pharmacological interventions can easily be applied to the Model to see the impacts Pakistan is currently in very early stage of the COVID-19. The growth rate of Pakistan is very low as compare to other countries. The SIR epidemic model shows that growth will increase exponentially and will reach 1000000 in the next 2 months and it will be difficult for Pakistan healthcare system to cope with the situation. This model also suggests that the Nonpharmacological Interventions (NPI) such as social distancing, complete lock down or imposing curfew, observing hygiene by washing hands, using hand sanitizers and wearing mask can slow down the propagation of the COVID-19 and can reduce the exposure of susceptible population to the infectious population. 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. Hence decreasing the contact rate and transmissibility c a n s u r e l y d e c l i n e t h e g r a p h f o r i n f e c t i o n s , h o s p i t a l i z a t i o n s , I C U a d m i s s i o n s a n d u l t i m a t e l y t h e d e c r e a s e i n m o r t a l i t y r a t e u p t o 9 0 % i n t h e n e x t t w o m o n t h s . Pathological findings of COVID-19 associated with acute respiratory distress syndrome. The Lancet respiratory medicine China Medical Treatment Expert Group for Covid-19. Clinical characteristics of coronavirus disease Acta bio-medica: Atenei Parmensis Containing papers of a mathematical and physical character Healthcare impact of COVID-19 epidemic in India: A stochastic mathematical model Forecasting COVID 19 growth in India using Susceptible-Infected-Recovered (SIR) model. arXiv, 2020: p Epidemic analysis of COVID-19 in China by dynamical modeling A simple Stochastic SIR model for COVID 19 Infection Dynamics for Karnataka: Learning from Europe Challenges faced by Pakistani healthcare system: Clinician's perspective Effect of non-pharmaceutical interventions for containing the COVID-19 outbreak: an observational and modelling study. medRxiv 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 May 13, 2020 The contact rate has been found by taking the data from people of all ages and gender both rural and urban population through a questioner and calculated the mean. So NPIs we just decrease the contact rate according to the situations. The value used, 2.0%, was estimated by comparing the Reproduction Number (R0) in community settings (1.4 to 3.9) with a normal contact rate whereas transmissibility and removal rate (inverse of duration of infectiousness) were assumed constant. Contact tracing data from 10 early cases in China showed the mean serial interval (time between successive cases) was 7.5 days with a SD of 3 Mortality rate 1.5% As of 8/04/2020, the average daily mortality rate of COVID19 is 1.5% COVID-19 has been between 1.4 to 3.9. R 0 is also an indication of the effectiveness of community interventions. An R 0 less than 1 indicate transmission has stopped.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. (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 May 13, 2020. . https://doi.org/10.1101/2020.05.08.20095794 doi: medRxiv preprint F i g u r e 2 A 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 May 13, 2020. 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 May 13, 2020. (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 May 13, 2020. . https://doi.org/10.1101/2020.05.08.20095794 doi: medRxiv preprint