Burden of COVID-19 and case fatality rate in Pune, India: an analysis of the first and second wave of the pandemic.

Objective: To assess trends in case incidence and fatality rate between the first and second waves, we analyzed programmatic COVID-19 data from Pune city, an epicenter of COVID-19 cases in India. Method: The trends of cases incidence, time-to-death and case fatality rate (CFR) were analyzed. Poisson regression models adjusted for age and gender were used to determine the independent effect of pandemic waves on mortality. Results: Of 465 192 COVID-19 cases, 162 182 (35%) were reported in the first wave and 4146 (2.5%) deaths, and 275 493 (59%) in the second wave and 3184 (1.1%) deaths (P<0.01). The overall CFR was 1.16 per 1000 person-days (PD), which declined from 1.80 per 1000 PD during the first wave to 0.77 per 1000 PD in the second. The risk of death was 1.49 times higher during the first wave (adjusted CFR ratio (aCFRR)1.49; 95% CI: 1.37-1.62) and 35% lower in the second wave (aCFRR 0.65; 95% CI: 0.59-0.70). Conclusion: The burden of COVID-19 cases and deaths was more significant in the second wave; however, the CFR declined as the pandemic progressed. Nevertheless, investigating new therapies and implementing mass vaccination against COVID-19 are urgently needed.

Association of national and regional lockdowns with COVID-19 infection rates in Pune, India.

Assessing the impact of lockdowns on COVID-19 incidence may provide important lessons for management of pandemic in resource-limited settings. We examined growth of incident confirmed COVID-19 patients before, during and after lockdowns during the first wave in Pune city that reported the largest COVID-19 burden at the peak of the pandemic. Using anonymized individual-level data captured by Pune's public health surveillance program between February 1st and September 15th 2020, we assessed weekly incident COVID-19 patients, infection rates, and epidemic curves by lockdown status (overall and by sex, age, and population density) and modelled the natural epidemic using the compartmental model. Effect of lockdown on incident patients was assessed using multilevel Poisson regression. We used geospatial mapping to characterize regional spread. Of 241,629 persons tested for SARS-CoV-2, 64,526 (26%) were positive, contributing to an overall rate of COVID-19 disease of 267·0 (95% CI 265·3-268·8) per 1000 persons. The median age of COVID-19 patients was 36 (interquartile range [IQR] 25-50) years, 36,180 (56%) were male, and 9414 (15%) were children < 18 years. Epidemic curves and geospatial mapping showed delayed peak of the patients by approximately 8 weeks during the lockdowns as compared to modelled natural epidemic. Compared to a subsequent unlocking period, incident COVID-19 patients were 43% lower (IRR 0·57, 95% CI 0·53-0·62) during India's nationwide lockdown and were 22% lower (IRR 0·78, 95% CI 0.73-0.84) during Pune's regional lockdown and was uniform across age groups and population densities. Both national and regional lockdowns slowed the COVID-19 infection rates in population dense, urban region in India, underscoring its impact on COVID-19 control efforts.

Just-in-time postnatal education programees to improve newborn care practices: needs and opportunities in low-resource settings.

Worldwide, many newborns die in the first month of life, with most deaths happening in low/middle-income countries (LMICs). Families' use of evidence-based newborn care practices in the home and timely care-seeking for illness can save newborn lives. Postnatal education is an important investment to improve families' use of evidence-based newborn care practices, yet there are gaps in the literature on postnatal education programees that have been evaluated to date. Recent findings from a 13 000+ person survey in 3 states in India show opportunities for improvement in postnatal education for mothers and families and their use of newborn care practices in the home. Our survey data and the literature suggest the need to incorporate the following strategies into future postnatal education programming: implement structured predischarge education with postdischarge reinforcement, using a multipronged teaching approach to reach whole families with education on multiple newborn care practices. Researchers need to conduct robust evaluation on postnatal education models incorporating these programee elements in the LMIC context, as well as explore whether this type of education model can work for other health areas that are critical for families to survive and thrive.