key: cord-1020163-jwrpwyo0 authors: Rath, Rama Shankar; Dixit, Anand Mohan; Koparkar, Anil Ramesh; Kharya, Pradip; Joshi, Hari Shanker title: COVID-19 pandemic in India: A Comparison of pandemic pattern in Selected States date: 2020-06-30 journal: Nepal J Epidemiol DOI: 10.3126/nje.v10i2.28960 sha: cbbe9c39ddbea59835fda079e87c15485a9eec5e doc_id: 1020163 cord_uid: jwrpwyo0 The COVID-19 pandemic currently expanded its roots to the 206 countries in the world. The morbidity and mortality are not only threat to humans but also its impact on economy is indirectly affecting us. The current review was done to find trend in various states of India. Data was collected from Ministry of Health and Family Welfare and descriptive analysis of the distribution of COVID-19 cases in different states of India. First case of COVID-19 was diagnosed in southernmost state Kerala and after that it has spread to all other states, but situations are more worsen in states with high international migration. Maharashtra is now the most affected state followed by Delhi. Among epidemic curve of all these states, Maharashtra has rapidly growing epidemic curve with highest slope, whereas Kerala has the lowest. When we compared the day wise cumulative case fatality rate, it was found that the case fatality rate of the states like Maharashtra, Madhya Pradesh & Rajasthan showed decrease in the case fatality rate over the period. Population density is also one of the key determinants of social interaction and thus the spread of disease specifically in communicable diseases. Government of India had taken many strong initiatives e.g. 40 days nation-wide lockdown, thermal screening at airport, announcement of relief packages for poor and quarantine of outsiders but still there are many missed opportunities like, early stoppage of international traffic, compulsory quarantine for all international travellers, better contact tracing, strong law and order and better preparedness plan. First case of Novel Corona Virus Disease (COVID- 19) was reported in December 2019 in Wuhan city of China [1] . Since then, the disease has caused significant concern in the world due to its pestilent nature. Novel Corona Virus pandemic has currently affected more than 200 countries. The disease is not only affecting health of the people but also affecting wealth of concern nation [2] . As of 20thJune 2020, a total of 85,25,042 confirmed cases and 4,56,973 deaths had taken place with no respite in geographical spread, mortality, morbidity, and economic loss due to the virus [3] . Among all the countries highest case load was reported in United States of America (USA) i.e. around 20,57,838 cases followed by, Brazil with 8,50,514 cases and Russian Federation with 5,37,210 cases [3] . India is 4th in the list with reported 3,32,424 cases and 9,520 deaths from novel coronavirus as of 15th June 2020, according to the Ministry of Health and Family Welfare, Government of India [4] . It has been considered that poverty and underdeveloped community are generally predispose to infectious diseases [5] . But persistent and rapid spread of infection of COVID-19 in developed countries with the damage caused to it has also shown the world that developed world are also not immune to the disease. Damage caused by COVID-19 is not only in the physical health but also psychological and socioeconomic in nature. However, a different pattern of the spread of the pandemic was observed in between the countries and within the country also [6] . Various inherent cultural and social differences might have resulted the same [7] . Similarly, public health policies also has some impact on the spread of the disease [8] [9] [10] . As health is a state subject, states within the country are free to take steps that is required to contain the pandemic spread over and above the policy of the central government [11] . Thus, the review was planned with the aim to compare the trend of the pandemic in different Indian States in early phases of the pandemic in India (till 15th June) and to assess the various possible factors for the same. This is a descriptive analysis of the distribution of COVID-19 cases in different states in India. Data was collected from the official website of Ministry of Health and Family Welfare (MOHFW), Government of India(GOI) on daily basis to extract the number of daily cases, recovered cases and deaths from which the total active cases were calculated [12] . Data was entered in Microsoft excel 2019 and analysis was done using both MS Excel and STATA 12. Cumulative Case load was calculated from daily case load. Case fatality rate was calculated state wise from the total cases and deaths reported in the same period and recovery rate was calculated. Cumulative case load was plotted against cumulative death to determine the date wise case fatality. Heat map of India was prepared with the help of the Microsoft Excel and Bing Maps. Operational Definition: 1. High Case Load States: Those states which reported more than 300 cases (arbitrarily selected) till 20/04/2020 were followed till 15/06/2020. 2. Day zero: When the state reported the 1st case of COVID-19. Defined as reported by the MOHFW, GOI. 3. Recovery rate: Total number of people reported to be recovered from the disease after the start of the epidemic divided by total number of cases reported by the state in the same period. 4. Case fatality rate: Total number deaths reported by the states divided by the total cases of COVID-19 in the same period. Literature searches India till now (15/06/2020) has reported 3,32,424 number of cases in a span of 132 days after the start of the pandemic in the country on 30/01/2020. States like Maharashtra, Delhi, Tamil Nadu, Madhya Pradesh, Gujarat, Rajasthan & Uttar Pradesh accounts for around 88.5% of case load in the country. Every state and union territory of India is currently affected by the pandemic till now although very few cases were reported in North eastern states like Meghalaya, Mizoram, Nagaland and union territories like Andaman Nicobar islands, Dadra and Nagar Haveli and Daman Diu [ Figure-1 ]. Highest burden of the cases was reported from Maharashtra (107958) followed by Tamil Nadu (44661) and Delhi (41182). Out of the total cases approximately 51% were either cured from disease or migrated whereas a total of 9520 deaths were reported leading to a case fatality rate of 2.9%. Onset of cases started in India from the last week of January, Kerala being the 1st state to report cases of COVID-19. Kerala also reported the 2nd and 3rd case of COVID-19 in 1st week of February. After a gap of nearly one-month Delhi reported the 4th case of India & its first case in the 1st week of March along with Telangana. Rajasthan Reported the 5th case of the country and 1st case of the state on 3rd March 2020. After this daily case were reported in the affected states. Uttar Pradesh reported 6 cases on 04/03/2020 and Haryana reported 14 cases on same day, highest reported in the country till date. Rest of the high case load states reported the cases after 10th of march. When we see the epidemic curve of all these states, Maharashtra has rapidly growing epidemic curve with highest slope followed by Tamil Nadu, Delhi, and Gujarat, whereas Kerala has the lowest slope of the epidemic curve although pandemic has started in each state on different days. Since the pandemic in different states started in different days, we tried to analyse the epidemic curve starting from day zero of each state i.e. from the day of reporting of cases by the state. We found that from all the states Madhya Pradesh has the sudden increase in slope starting from day 21 followed by Gujrat which showed a rise on day 23 followed by Maharashtra on day 25th. Kerala showed a long phase of slow growing epidemic followed by a slow rise in identified cases from the 50th day of the epidemic. Rest of the high burden states showed a slope which is in between the slope of Kerala and Maharashtra. [ Figure- 3] However in the later stage i.e. after 33rd day the case load in Maharashtra started growing at a rapid rate than all other states. Cases in states like Tamil Nadu and in the later stage i.e. around 60th day of the pandemic of the state. Rest all the states have shown a late rise in the case load i.e. around 75th day of the pandemic. Kerala continue to have a slow growing epidemic till now. Comparison of Outcome of the Patients in different states: Among the selected states Gujarat reported highest case fatality rate around 6.3% followed by West Bengal (4.3%) and Madhya Pradesh (4.2%). Kerala showed the lowest case fatality rate i.e. around 0.8%. The proportion of cases recovered from the disease is around 75.4% in Rajasthan which is highest in the country, followed by Madhya Pradesh 71.1% and Gujarat which is around 69.4%. Delhi showed the Lowest recovery rate of around 38.4% preceded by Kerala with recovery rate of 44.8%. When we compared the day wise cumulative case fatality rate day-wise we found that the case fatality rate of Delhi and Tamil Nadu increased over the period, whereas Maharashtra, Gujarat, Jammu & Kashmir and Uttar Pradesh maintained a constant death rate over the period. Death rate of Madhya Pradesh and West Bengal decreased over the period. For rest of the states due to very low number of cases and death it is very difficult to comment on the case fatality rate over the period. . From these, 109 districts were from high burden states and 55 districts (50%) has population density more than 500 [22] . Similarly, the large outbreaks were reported in the cities like Mumbai, Delhi, Kolkata and Chennai accounting to around one lakh cases in the countries. These cities were also reported to have high population density according to census 2011 [23] . Initiation of pandemic depended up on the in-migration but the progression of pandemic generally depends up on different strategies adopted by the states to stop the transmission. HSJ, AMD, RSR conceptualized the study. RSR, PK, ARK extracted data from various sources and drafted the manuscript. All Authors made substantial contribution to the study and manuscript in each stage by giving the critical input and adding the intellectual content to it. 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