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

Conventional and frugal methods of estimating COVID-19-related excess deaths and undercount factors

Across the world, the officially reported number of COVID-19 deaths is likely an undercount. Establishing true mortality is key to improving data transparency and strengthening public health systems to tackle future disease outbreaks. In this study, we estimated excess deaths during the COVID-19 pandemic in the Pune region of India. Excess deaths are defined as the number of additional deaths relative to those expected from pre-COVID-19-pandemic trends. We integrated data from: (a) epidemiological modeling using pre-pandemic all-cause mortality data, (b) discrepancies between media-reported death compensation claims and official reported mortality, and (c) the "wisdom of crowds" public surveying. Our results point to an estimated 14,770 excess deaths [95% CI 9820-22,790] in Pune from March 2020 to December 2021, of which 9093 were officially counted as COVID-19 deaths. We further calculated the undercount factor-the ratio of excess deaths to officially reported COVID-19 deaths. Our results point to an estimated undercount factor of 1.6 [95% CI 1.1-2.5]. Besides providing similar conclusions about excess deaths estimates across different methods, our study demonstrates the utility of frugal methods such as the analysis of death compensation claims and the wisdom of crowds in estimating excess mortality.

Effectiveness of social distancing measures and lockdowns for reducing transmission of COVID-19 in non-healthcare, community-based settings

Social distancing measures (SDMs) are community-level interventions that aim to reduce person-to-person contacts in the community. SDMs were a major part of the responses first to contain, then to mitigate, the spread of SARS-CoV-2 in the community. Common SDMs included limiting the size of gatherings, closing schools and/or workplaces, implementing work-from-home arrangements, or more stringent restrictions such as lockdowns. This systematic review summarized the evidence for the effectiveness of nine SDMs. Almost all of the studies included were observational in nature, which meant that there were intrinsic risks of bias that could have been avoided were conditions randomly assigned to study participants. There were no instances where only one form of SDM had been in place in a particular setting during the study period, making it challenging to estimate the separate effect of each intervention. The more stringent SDMs such as stay-at-home orders, restrictions on mass gatherings and closures were estimated to be most effective at reducing SARS-CoV-2 transmission. Most studies included in this review suggested that combinations of SDMs successfully slowed or even stopped SARS-CoV-2 transmission in the community. However, individual effects and optimal combinations of interventions, as well as the optimal timing for particular measures, require further investigation. This article is part of the theme issue 'The effectiveness of non-pharmaceutical interventions on the COVID-19 pandemic: the evidence'.

COVID-19 Pandemic: Did Strict Mobility Restrictions Save Lives and Healthcare Costs in Maharashtra, India?

INTRODUCTION

Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown's impact on COVID-19 cases and associated healthcare costs.

METHODS

Using daily case data for 84 days (9 March-31 May 2020), we modeled the epidemic's trajectory and predicted new cases for different phases of lockdown. We fitted log-linear models to estimate the growth rate, basic (R₀), daily reproduction number (R_e), and case doubling time. Based on pre-restriction and Phase 1 R₀, we predicted new cases for the rest of the restriction phases, and we compared them with the actual number of cases during each phase. Furthermore, using the published and gray literature, we estimated the costs and savings of implementing these restrictions for the projected period, and we performed a sensitivity analysis.

RESULTS

The estimated median R₀ during the different phases was 1.14 (95% CI: 0.85, 1.45) for pre-lockdown, 1.67 (95% CI: 1.50, 1.82) for phase 1 (strict mobility restrictions), 1.24 (95% CI: 1.12, 1.35) for phase 2 (extension of phase 1 with no restrictions on agricultural and essential services), 1.12 (95% CI: 1.01, 1.23) for phase 3 (extension of phase 2 with mobility relaxations in areas with few infections), and 1.05 (95% CI: 0.99, 1.123) for phase 4 (implementation of localized lockdowns in high-case-load areas with fewer restrictions on other areas), respectively. The corresponding doubling time rate for cases (in days) was 17.78 (95% CI: 5.61, -15.19), 3.87 (95% CI: 3.15, 5.00), 10.37 (95% CI: 7.10, 19.30), 20.31 (95% CI: 10.70, 212.50), and 45.56 (95% CI: 20.50, -204.52). For the projected period, the cases could have reached 631,819 without the lockdown, as the actual reported number of cases was 64,975. From a healthcare perspective, the estimated total value of averted cases was INR 194.73 billion (USD 2.60 billion), resulting in net cost savings of 84.05%. The Incremental Cost-Effectiveness Ratio (ICER) per Quality Adjusted Life Year (QALY) for implementing the lockdown, rather than observing the natural course of the pandemic, was INR 33,812.15 (USD 450.83).

CONCLUSION

Maharashtra's early public health response delayed the pandemic and averted new cases and deaths during the first wave of the pandemic. However, we recommend that such restrictions be carefully used while considering the local socio-economic realities in countries like India.

Plausible explanation for the third COVID-19 wave in India and its implications

Recently some of us used a random-walk Monte Carlo simulation approach to study the spread of COVID-19. The calculations were reasonably successful in describing secondary and tertiary waves of infection, in countries such as the USA, India, South Africa and Serbia. However, they failed to predict the observed third wave for India. In this work we present a more complete set of simulations for India, that take into consideration two aspects that were not incorporated previously. These include the stochastic movement of an erstwhile protected fraction of the population, and the reinfection of some recovered individuals because of their exposure to a new variant of the SARS-CoV-2 virus. The extended simulations now show the third COVID-19 wave for India that was missing in the earlier calculations. They also suggest an additional fourth wave, which was indeed observed during approximately the same time period as the model prediction.

Uneven Implications of Lockdown Amid COVID-19 in India: From Harassment, Stigma, Crime, and Internally Displaced People to Stress and Coping Strategies in the Middle/Upper Class

A content analysis of an English Newspaper, The Times of India (the world's largest newspaper by circulation) during the first national lockdown amid the COVID-19 pandemic identified nine different categories culled out from a total of 129 news categories reporting unprecedented COVID-19 stories. Half of them portrayed two sides of a coin: from daily wagers and migrant workers, including internally displaced people (23/129), harassment and stigma (4/129), and crime (3/129) to stressors and coping strategies for middle/upper class individuals (39/129). Reports evidenced increased vulnerability in the lower layers of Indian stratified society. Yet, two years later, the uneven implications on physical and mental health are scarcely studied by scientific researchers.

ATP-binding cassette (ABC) drug transporters in the developing blood-brain barrier: role in fetal brain protection

The blood-brain barrier (BBB) provides essential neuroprotection from environmental toxins and xenobiotics, through high expression of drug efflux transporters in endothelial cells of the cerebral capillaries. However, xenobiotic exposure, stress, and inflammatory stimuli have the potential to disrupt BBB permeability in fetal and post-natal life. Understanding the role and ability of the BBB in protecting the developing brain, particularly with respect to drug/toxin transport, is key to promoting long-term brain health. Drug transporters, particularly P-gp and BCRP are expressed in early gestation at the developing BBB and have a crucial role in developmental homeostasis and fetal brain protection. We have highlighted several factors that modulate drug transporters at the developing BBB, including synthetic glucocorticoid (sGC), cytokines, maternal infection, and growth factors. Some factors have the potential to increase expression and function of drug transporters and increase brain protection (e.g., sGC, transforming growth factor [TGF]-β). However, others inhibit drug transporters expression and function at the BBB, increasing brain exposure to xenobiotics (e.g., tumor necrosis factor [TNF], interleukin [IL]-6), negatively impacting brain development. This has implications for pregnant women and neonates, who represent a vulnerable population and may be exposed to drugs and environmental toxins, many of which are P-gp and BCRP substrates. Thus, alterations in regulated transport across the developing BBB may induce long-term changes in brain health and compromise pregnancy outcome. Furthermore, a large portion of neonatal adverse drug reactions are attributed to agents that target or access the nervous system, such as stimulants (e.g., caffeine), anesthetics (e.g., midazolam), analgesics (e.g., morphine) and antiretrovirals (e.g., Zidovudine); thus, understanding brain protection is key for the development of strategies to protect the fetal and neonatal brain.