Dynamics and Transmission of COVID-19_VRN.pptx

TRANSMISSION

1. Impact of Changing Dynamics COVID-19 Spread in Pune Municipal Corporation Pune Maharashtra, India Dr. Virendra R. Nagarale Professor Department of Geography, S.N.D.T. Women’s University Pune Campus, Pune INDIA 411038 [email protected]

2. Introduction The 21st century is continuously facing uncertain crisis. One of that is Covid -19 pandemic which has created severe impact globally. The world economy is paralysed due to widespread transmission of coronavirus . Many efforts have been made by the authorities to stop the spread resulting in lockdown, quarantine, social distancing, restrictions on work and transportation, Communication lock etc. Cities are facing enormous problems due to lack of space and increased population spreading of pandemic at its peak. The urban areas with dense population and compact household sizes are more prone to several problems and create numerous challenges. The urban mobility is suddenly stopped due to increased transmission of coronavirus and hence the administration is failed to coped up with the situation. The study seek to understand the spread of coronavirus in association with the demographic characteristics and to understand the administrative ward wise pattern of transmission by using GIS tool.

3. Major Research Works Reviewed Stojkoski et. al. (May, 2020) identified 29 potential determinants that describes a diverse ensemble of social and economic factors: Demographic structure, societal characteristics, economic performance, healthcare infrastructure etc. Using a technique Bayesian model averaging (BMA) they measured the duration of pandemics in a country simply as the number of days since the first registered case, whereas in order to assess the effect of government restrictions we construct a stringency index. The authors argue that the demographic structure may impact the average susceptibility of the population to a disease . The article discuses that more populated economies show greater resistance to being infected by the virus, whereas countries with larger government expenditure display greater susceptibility to the virus infection. This is because of structured populations. But some countries do not follow the exact social network structures within a population. Harapan H. et.al. (2020) The authors provide an exhaustive review of literature extending from the origin to the transmission and treatment,, diagnosis and management of the disease. This review summarizes the effect, factors, control measures etc. from publicly available information. Such type of review work is most useful in building theoretical understanding of the community and researchers. The study made by Li S. et al. (2020), shows how the undocumented infectious cases of COVID-19 facilitated the geographic spread of the epidemic in China . The authors used a networked dynamic meta-population model and Bayesian inference from which they found that 86% of all infections were undocumented before the Wuhan lockdown and reported infections would have been reduce by 78.7% in China, without transmission from undocumented cases between January 10 and January 23. Fang H. et.al. (March, 2020) quantifies the causal impact of human mobility restrictions, particularly at the lockdown period in Wuhan. The result shows that the lockdown of Wuhan reduced inflow into Wuhan by 76.64%, outflows from Wuhan by 56.35%, and within-Wuhan movements by 54.15%.

4. Study Area Pune city is partly governed by Pune Municipal Corporation which is divided into 15 administrative and 144 electoral wards and those wards are maintained by some prime functional departments. The administrative wing of PMC Pune Municipal Corporation is located in Pune District in western region in Maharashtra state between 17 50’ North to 19 24’ North latitude and 73 19’ East to 75 10’ East longitudes. The city is located to the South-East of Mumbai at an elevation of 560 m above mean sea level. Pune is the eighth largest city in India and second in Maharashtra State in terms of population.

5. Total population of PMC is increases from 1951 to 2011, in 1951 it was 488,419 and in next six decades it is observed that the population increases in every decade. In 2011, total population of PMC is 3124458 as against 2374013 in 2001. In October 2018, PMC included 11 fringing areas (Villages) to its administrative limits adding 239483 more population residing in 57928 households. The total population of PMC as in year 2018 is 3371626. Total SC and ST population is 420765 and 34129 respectively. The total area of PMC was 243.96 sq.km. and after the addition of eleven villages in the year 2018 now PMC governs 331.26 sq. km area.

6. Map of Study Area Pune Cantonment

7. Sr. No. Administrative Ward Electoral Wards Total Population SC Population ST Population 1 NagarRoad 3,4,5 275938 30265 2244 2 Sangamwadi-Yerwada 1,2,6 253778 56108 4431 3 Dhole Patil Road 20,21 155160 37164 2020 4 Aundh 8,9 169432 23557 2960 5 Ghole Road 7,14 169891 26104 2601 6 Kothrud 10,11,12 236606 17074 1829 7 Dhanakawadi-Sahakarnagar 35,39,40 263966 31198 2199 8 Sinhagad Road 30,33,34 244926 24665 2081 9 Warje Karve Nagar 13,31,32 248451 15619 2666 10 Hadapsar 22,23,26 368091 25973 2791 11 Wanawadi 24,25,27 204644 25925 1712 12 Yevalewadi 38,41 154303 19507 1946 13 Kasba-Vishrambaugh 15,16,29 214275 23382 1855 14 Bhavani Peth 17,18,19 211910 29791 986 15 Bibwewadi 28,36,37 200255 34433 1808     Totals   3371626 420765 34129 Population of PMC

8. Ward wise Positive Patients Summary As of June 21, 2020

9. Age and Sex-wise Distribution of Positive Patients As of April 24, 2020

10. Positive Cases Trend As of May 15, 2020

11. Positive Cases Trend As of May 28, 2020

12. Ward wise Distribution of Positive Cases in PMC As of June 21, 2020

13. Ward wise Distribution of Positive Cases in PMC As of July 8, 2020

14. PMC Ward wise Positive Cases on 1 st Sept. 2020

15. Months Pune City PCMC Pune District Deaths March to June 18062 2945 1913 903 July 36213 18269 7853 1180 August 41098 28116 15825 2052 September 49918 28751 35058 2394 Total 145291 78081 60649 6529 Regional Scenario of Total Infections and Deaths Period Positivity Rate (%) 28th Aug - 3 Sept 27.2 4 Sept - 10 Sept 30.5 11 Sept - 17 Sept 30.2 18 Sept - 24 Sept 28.2 25 Sept - 29 Sept 25.3

16. Observations At the beginning period of cononavirus spread and transmission in the months of March and April the administrative wards of Bhavani Peth and Kasba Vishrambaug is seen to be more vulnerable. Whereas, the wards such as Aundh- Baner , Warje-Karvenagar and Kothrud Bavdhan is seen to be more resistant. It has been observed that the areas having small size and large proportion of population which proves to be a high density area are more susceptible to the spread and transmission coronavirus . For example, Bhavani Peth and Kasba Vishrambaug has comaritively small area and the population is quit higher and also the trend of active patients are also higher in those areas. The location of the area also plays major role in the spread and transmission of coronavirus . The peripheral areas are acted as more resistant regions to be infected from the virus whereas the centrally located areas ( Prabhag ) shows more succeptible to the transmission. The no. of deaths ocuured due to coronavirus is seen to be skewed towards high population density areas as well as high population areas such as Bhavani Peth and Hadapsar-Mundhva administrative wards.

17. The age and sex-wise distribution of active patients shows that the age group of 21-30, 31-40 and 41-50 are more susceptible to the spread and transmission of coronavirus . Whereas, the age group of 51-60 and 61-70 age groups are more vulnerable to deaths. The male active patients are higher than that of females but the numbers for female active patients are quit higher in 51-60 age group. It has been observed that the no. of active patients has increased four to five time in the time span of 18 days from 9 th April to 27 th April. In the month of May 2020 the increased trend of positive cases is observed which is trippled in 28 days i.e. from 1 st May to 28 th May 2020. In the month of June the patients were increased in the slum areas such as Tadiwala Road ( Dhole Patil Road), Shivaji Nagar-Ghole road and Yerwada-Kalas – Dhanori . Till 8 th July 2020 the no. of patients has been increased drastically in the wards which have high population density as well as high proportion of population. Moreover the slum areas are also seen to be more susceptible to the spread of coronavirus .

18. The first week of the month September shows peak increase in the no. of positive cases which is more than 2000 a day. Whereas, next phase of transmission in the month of September is seen to be decreasing. On 9 th Sept. the total positive cases were 2078 which has been decreased to 1898 on 12 th , 1100 on 14 th and 1040 on 29 th Sept. Although the dynamics has been observed in this period from 8 th Sept. to 29 th but overall the no. of cases has been decreased drastically. Apart from the transmission the recovery rate has also been increased in the month of Sept. 2020. According to the news on 1 st Oct, 1.25 patients were recovered from this pandemic. Recently there are only 15 % active patient in PMC. Moreover the no. of patients kept on oxygen has also been released to the normal situation. The decreasing trend of positive patients has lead to unlock many businesses and also extended freedom to many a services in PMC. It includes opening of Bar, Restaurants and Hotels to provide full service of dine-in following all the guidelines of government regarding the precautions and handling of food. Still there are restrictions over the educational institutions, theatres and other public social gatherings but if the trend of transimission will get decrease then it will be helpful for lessening the restrictions over all these services.

19. Conclusion Demographic characteristics and its spatial distribution plays key role in policy formulation and decision making. The present study tried explore the demographic characteristics which are favourable / promoting the spread of coronavirus in PMC. The study addressed urban spatial arrangements of households and demographic characteristics and it is also seen that the density of a population is directly proportional to the spread and transmission of coronavirus . The dynamics of spread and transmission of coronavirus can be seen with the help of demographic characteristics like age and sex-wise distribution of infected people. This study also explores various dimensions to conduct a research in the filed of urban demographics. The tools of GIS is helpful in the process of policy formation as well as its implementation.

20. Bibliography City Population Census 2011, P.M.C. Pune. Fang, Hanming, Long Wang, and Yang Yang. “Human Mobility Restrictions And The Spread Of The Novel Coronavirus ( 2019-Nov ) In China.” National Bureau Of Economic Research , NBER Working Paper No. 26906 , March 2020 . http://www.nber.org/papers/w26906 . General Election of PMC: Population Data Harapan , Harapan , Naoya Itoh , Amanda Yufika , Wira Winardi , Synat Keam , Haypheng Te, Dewi Megawati, Zinatul Hayati , Abram L. Wagner, and Mudatsir Mudatsir . “ Coronavirus Disease 2019 (COVID-19): A Literature Review.” Journal of Infection and Public Health 13, no. 5 (May 2020): 667–73. https://doi.org/10.1016/j.jiph.2020.03.019 . Lai, S., N. W. Ruktanonchai , L. Zhou, O. Prosper, W. Luo , J. R. Floyd, A. Wesolowski , M. Santillana , C. Zhang, X. Du, H. Yu, and T. A. J (2020). E_ect of non-pharmaceutical interventions for containing the covid-19 outbreak in china. doi : https://doi.org/10.1101/2020.03.03.20029843, medRxiv . Posts: ‘PMC Pune’ Facebook page. Stojkoski , Viktor, Zoran Utkovski , Petar Jolakoski , Dragan Tevdovski , and Ljupco Kocarev . “The Socio-Economic Determinants of the Coronavirus Disease (COVID-19) Pandemic.” ArXiv:2004.07947 [Physics, q-Fin, Stat] , May 5, 2020. http://arxiv.org/abs/2004.07947 .

21. Thank You…