Understanding the Prevalence and Geographic Heterogeneity of SARS-CoV-2 Infection: Findings of the First Serosurvey in Uttar Pradesh, India.

Population-based serological antibody test for SARS-CoV-2 infection helps in estimating the exposure in the community. We present the findings of the first district representative seroepidemiological survey conducted between 4 and 10 September 2020 among the population aged 5 years and above in the state of Uttar Pradesh, India. Multi-stage cluster sampling was used to select participants from 495 primary sampling units (villages in rural areas and wards in urban areas) across 11 selected districts to provide district-level seroprevalence disaggregated by place of residence (rural/urban), age (5-17 years/aged 18 +) and gender. A venous blood sample was collected to determine seroprevalence. Of 16,012 individuals enrolled in the study, 22.2% [95% CI 21.5-22.9] equating to about 10.4 million population in 11 districts were already exposed to SARS-CoV-2 infection by mid-September 2020. The overall seroprevalence was significantly higher in urban areas (30.6%, 95% CI 29.4-31.7) compared to rural areas (14.7%, 95% CI 13.9-15.6), and among aged 18 + years (23.2%, 95% CI 22.4-24.0) compared to aged 5-17 years (18.4%, 95% CI 17.0-19.9). No differences were observed by gender. Individuals exposed to a COVID confirmed case or residing in a COVID containment zone had higher seroprevalence (34.5% and 26.0%, respectively). There was also a wide variation (10.7-33.0%) in seropositivity across 11 districts indicating that population exposed to COVID was not uniform at the time of the study. Since about 78% of the population (36.5 million) in these districts were still susceptible to infection, public health measures remain essential to reduce further spread.

Addressing the social determinants of health through health system strengthening and inter-sectoral convergence: the case of the Indian National Rural Health Mission.

BACKGROUND: At the turn of the 21st century, India was plagued by significant rural-urban, inter-state and inter-district inequities in health. For example, in 2004, the infant mortality rate (IMR) was 24 points higher in rural areas compared to urban areas. To address these inequities, to strengthen the rural health system (a major determinant of health in itself) and to facilitate action on other determinants of health, India launched the National Rural Health Mission (NRHM) in April 2005. METHODS: Under the NRHM, Rs. 666 billion (US$12.1 billion) was invested in rural areas from April 2005 to March 2012. There was also a substantially higher allocation for 18 high-focus states and 264 high-focus districts, identified on the basis of poor health and demographic indicators. Other determinants of health, especially nutrition and decentralized action, were addressed through mechanisms like State/District Health Missions, Village Health, Sanitation and Nutrition Committees, and Village Health and Nutrition Days. RESULTS: Consequently, in bigger high-focus states, rural IMR fell by 15.6 points between 2004 and 2011, as compared to 9 points in urban areas. Similarly, the maternal mortality rate in high-focus states declined by 17.9% between 2004-2006 and 2007-2009 compared to 14.6% in other states. CONCLUSION: The article, on the basis of the above approaches employed under NRHM, proposes the NRHM model to 'reduce health inequities and initiate action on SDH'.