Pub Date : 2020-06-19DOI: 10.1101/2020.06.15.20132308
Km Sulaiman, T. Muhammad, Rishad Muhammad A P, K. Afsal
Kerala reported the first three cases of coronavirus in India in late January. Kerala, one of the India’s most densely populated states, which makes its success in fighting the Covid-19 all the more commendable. Moreover, an estimated 17% of its 35 million population employed or lives elsewhere, more than 1 million tourists visit each year, and hundreds of students study abroad, including in China. All of this mobility makes the state more vulnerable to contagious outbreaks. What is the strategy behind the success story? This paper compares the situation of COVID-19 pandemic in major states and Kerala by the different phase of lockdown, and also highlights Kerala’s fight against the pandemic. We used publicly available data from https://www.covid19india.org/ and Covid-19 Daily Bulletin (Jan 31-May 31), Directorate of Health Services, Kerala (https://dashboard.kerala.gov.in/). We calculate the phase-wise period prevalence rate (PPR) and the case fatality rate (CFR) of the last phase. Compared to other major states, Kerala showed better response in preventing pandemic. The equation for the Kerala’s success has been simple, prioritized testing, widespread contact tracing, and promoting social distance. They also imposed uncompromising controls, were supported by an excellent healthcare system, government accountability, transparency, public trust, civil rights and importantly the decentralized governance and strong grass-root level institutions. The “proactive” measures taken by Kerala such as early detection of cases and extensive social support measures can be a “model for India and the world”.
{"title":"Trace, Quarantine, Test, Isolate and Treat: A Kerala Model of Covid-19 Response","authors":"Km Sulaiman, T. Muhammad, Rishad Muhammad A P, K. Afsal","doi":"10.1101/2020.06.15.20132308","DOIUrl":"https://doi.org/10.1101/2020.06.15.20132308","url":null,"abstract":"Kerala reported the first three cases of coronavirus in India in late January. Kerala, one of the India’s most densely populated states, which makes its success in fighting the Covid-19 all the more commendable. Moreover, an estimated 17% of its 35 million population employed or lives elsewhere, more than 1 million tourists visit each year, and hundreds of students study abroad, including in China. All of this mobility makes the state more vulnerable to contagious outbreaks. What is the strategy behind the success story? This paper compares the situation of COVID-19 pandemic in major states and Kerala by the different phase of lockdown, and also highlights Kerala’s fight against the pandemic. We used publicly available data from https://www.covid19india.org/ and Covid-19 Daily Bulletin (Jan 31-May 31), Directorate of Health Services, Kerala (https://dashboard.kerala.gov.in/). We calculate the phase-wise period prevalence rate (PPR) and the case fatality rate (CFR) of the last phase. Compared to other major states, Kerala showed better response in preventing pandemic. The equation for the Kerala’s success has been simple, prioritized testing, widespread contact tracing, and promoting social distance. They also imposed uncompromising controls, were supported by an excellent healthcare system, government accountability, transparency, public trust, civil rights and importantly the decentralized governance and strong grass-root level institutions. The “proactive” measures taken by Kerala such as early detection of cases and extensive social support measures can be a “model for India and the world”.","PeriodicalId":81085,"journal":{"name":"Demography India","volume":"67 1","pages":"120-131"},"PeriodicalIF":0.0,"publicationDate":"2020-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84067109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Assuming that the expiration of lactation is caused by 2 competing forces a model is presented to estimate with best possible precision the mean period of natural infecundability following childbirth. In general a lactating mother following childbirth is considered infecundable. Sometimes however menstruation may freshly recommence before the end of the period of lactation and place the mother at risk of reconception. Assuming that post partum amenorrhoea (PPA) expires sometime soon after the end of lactation what is the expected longevity of the lactation period? This mathematical model offers a solution to estimating both the mean length of PPA when lactation period continues after the end of the former. The model accomplishes this task by weighting the mean infecundable period with the respective probabilities that lactation will last longer that PPA or vice versa. A precise estimation lies somewhere between the 2 scenarios. Freunds 1961 bivariate exponential model is used to illustrate the methodology.
{"title":"On the estimation of mean infecundable period following childbirth.","authors":"S. Biswas, A. Ma","doi":"10.1002/BIMJ.4710330609","DOIUrl":"https://doi.org/10.1002/BIMJ.4710330609","url":null,"abstract":"Assuming that the expiration of lactation is caused by 2 competing forces a model is presented to estimate with best possible precision the mean period of natural infecundability following childbirth. In general a lactating mother following childbirth is considered infecundable. Sometimes however menstruation may freshly recommence before the end of the period of lactation and place the mother at risk of reconception. Assuming that post partum amenorrhoea (PPA) expires sometime soon after the end of lactation what is the expected longevity of the lactation period? This mathematical model offers a solution to estimating both the mean length of PPA when lactation period continues after the end of the former. The model accomplishes this task by weighting the mean infecundable period with the respective probabilities that lactation will last longer that PPA or vice versa. A precise estimation lies somewhere between the 2 scenarios. Freunds 1961 bivariate exponential model is used to illustrate the methodology.","PeriodicalId":81085,"journal":{"name":"Demography India","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"1989-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/BIMJ.4710330609","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50828104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sex preference in relation to desire for additional children in urban India.","authors":"S. Lahiri","doi":"10.2307/1965952","DOIUrl":"https://doi.org/10.2307/1965952","url":null,"abstract":"","PeriodicalId":81085,"journal":{"name":"Demography India","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"1975-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.2307/1965952","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"68398368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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