Assessing New York City's COVID-19 Vaccine Rollout Strategy: A Case for Risk-Informed Distribution.

This study reviews the impact of eligibility policies in the early rollout of the COVID-19 vaccine on coverage and probable outcomes, with a focus on New York City. We conducted a retrospective ecological study assessing age 65+, area-level income, vaccination coverage, and COVID-19 mortality rates, using linked Census Bureau data and New York City Health administrative data aggregated at the level of modified zip code tabulation areas (MODZCTA). The population for this study was all individuals in 177 MODZCTA in New York City. Population data were obtained from Census Bureau and New York City Health administrative data. The total mortality rate was examined through an ordinary least squares (OLS) regression model, using area-level wealth, the proportion of the population aged 65 and above, and the vaccination rate among this age group as predictors. Low-income areas with high proportions of older people demonstrated lower coverage rates (mean vaccination rate 52.8%; maximum coverage 67.9%) than wealthier areas (mean vaccination rate 74.6%; maximum coverage 99% in the wealthiest quintile) in the first 3 months of vaccine rollout and higher mortality over the year. Despite vaccine shortages, many younger people accessed vaccines ahead of schedule, particularly in high-income areas (mean coverage rate 60% among those 45-64 years in the wealthiest quintile). A vaccine program that prioritized those at greatest risk of COVID-19-associated morbidity and mortality would have prevented more deaths than the strategy that was implemented. When rolling out a new vaccine, policymakers must account for local contexts and conditions of high-risk population groups. If New York had focused limited vaccine supply on low-income areas with high proportions of residents 65 or older, overall mortality might have been lower.

Designing a Pro-Equity HPV Vaccine Delivery Program for Girls Who Have Dropped Out of School: Community Perspectives From Uttar Pradesh, India.

India experiences a substantial burden of cervical cancer and accounts for nearly one third of cervical cancer deaths worldwide. While human papillomavirus (HPV) vaccines have been introduced subnationally in some states, HPV has not yet been rolled out nationally. Given the target age group, schools are the most common delivery channel for HPV vaccines, but this fails to account for local girls who never attended or no longer attend school. We conducted a qualitative, design-informed, community-based study conducted in Uttar Pradesh, India. We assessed facilitators and barriers among out-of-school girls and proposed program characteristics to inform the design of pro-equity HPV vaccine delivery programs for out-of-school girls. Programs should improve parental knowledge of the risk of cervical cancer, engage vaccinated girls as vaccine champions, utilize varied media options for low-literacy populations, and ensure that HPV vaccine services are accessible and flexible to accommodate out-of-school girls. In areas with poor or irregular school attendance among adolescent girls, HPV vaccine coverage will remain suboptimal until programs can effectively address their needs and reach this priority population. Our findings present a meaningful opportunity for program planners to purposefully design HPV vaccination programs according to these parameters, rather than modifying existing programs to include HPV vaccine. Adolescent girls, their parents, and other community members should be involved in program design to ensure that the program can effectively meet the needs of adolescent girls who are not in school.

Artificial intelligence and the future of global health.

Concurrent advances in information technology infrastructure and mobile computing power in many low and middle-income countries (LMICs) have raised hopes that artificial intelligence (AI) might help to address challenges unique to the field of global health and accelerate achievement of the health-related sustainable development goals. A series of fundamental questions have been raised about AI-driven health interventions, and whether the tools, methods, and protections traditionally used to make ethical and evidence-based decisions about new technologies can be applied to AI. Deployment of AI has already begun for a broad range of health issues common to LMICs, with interventions focused primarily on communicable diseases, including tuberculosis and malaria. Types of AI vary, but most use some form of machine learning or signal processing. Several types of machine learning methods are frequently used together, as is machine learning with other approaches, most often signal processing. AI-driven health interventions fit into four categories relevant to global health researchers: (1) diagnosis, (2) patient morbidity or mortality risk assessment, (3) disease outbreak prediction and surveillance, and (4) health policy and planning. However, much of the AI-driven intervention research in global health does not describe ethical, regulatory, or practical considerations required for widespread use or deployment at scale. Despite the field remaining nascent, AI-driven health interventions could lead to improved health outcomes in LMICs. Although some challenges of developing and deploying these interventions might not be unique to these settings, the global health community will need to work quickly to establish guidelines for development, testing, and use, and develop a user-driven research agenda to facilitate equitable and ethical use.

National and provincial impact and cost-effectiveness of Haemophilus influenzae type b conjugate vaccine in China: a modeling analysis.

BACKGROUND: Globally, Haemophilus influenzae type b (Hib) vaccine has substantially reduced the burden of Hib invasive disease. However, China remains the only country not to include Hib vaccine into its national immunization program (NIP), although it accounts for 11% of global Hib deaths. We aimed to assess the cost-effectiveness of including Hib vaccine in China's NIP at the national and provincial levels. METHODS: Using a decision-tree Markov state transition model, we estimated the cost-effectiveness of Hib vaccine in the NIP compared to the status quo of Hib vaccine in the private market for the 2017 birth cohort. Treatment costs and vaccine program costs were calculated from Chinese Center for Disease Control and Prevention (CDC) and national insurance databases. Epidemiological data and other model parameters were obtained from published literature. Cases and deaths averted, quality-adjusted life years (QALYs) gained, and incremental cost-effectiveness ratios (ICER) were predicted by province. Deterministic and probabilistic sensitivity analyses were performed to explore model uncertainty. RESULTS: Including Hib vaccine in the NIP was projected to prevent approximately 2700 deaths (93% reduction) and 235,700 cases of Hib disease (92% reduction) for the 2017 birth cohort at the national level. Hib vaccine was cost-effective nationally (US$ 8001 per QALY gained) compared to the GDP per capita and cost-effective in 15 of 31 provinces. One-way and scenario sensitivity analyses indicated results were robust when varying model parameters, and in probabilistic sensitivity analysis, Hib vaccine had a 64% probability of being cost-effective nationally. CONCLUSION: Introducing Hib vaccine in China's NIP is cost-effective nationally and in many provinces. Less socioeconomically developed provinces with high Hib disease burden and low access to Hib vaccine in the current private market, such as those in the west region, would benefit the most from adding Hib vaccine to the NIP. In the absence of a national policy decision on Hib vaccine, this analysis provides evidence for provincial governments to include Hib vaccine into local immunization programs to substantially reduce disease burden and treatment costs.

Change in full immunization inequalities in Indian children 12-23 months: an analysis of household survey data.

BACKGROUND: India has made substantial progress in improving child health in recent years. However, the country continues to account for a large number of vaccine preventable child deaths. We estimated wealth-related full immunization inequalities in India. We also calculated the degree to which predisposing, reinforcing, and enabling factors contribute to these inequalities. METHODS: We used data from the two rounds of a large nationally representative survey done in all states in India in 2005-06 (n = 9582) and 2015-16 (n = 49,284). Full immunization status was defined as three doses of diphtheria-tetanus-pertussis vaccine, three doses of polio vaccine, one dose of Bacillus Calmette-Guérin vaccine, and one dose of measles vaccine in children 12-23 months. We compared full immunization coverage by wealth quintiles using descriptive statistics. We calculated concentration indices for full immunization coverage at the national and state levels. Using predisposing, reinforcing, and enabling factors associated with full immunization status identified from the literature, we applied a generalized linear model (GLM) framework with a binomial distribution and an identity link to decompose the concentration index. RESULTS: National full immunization coverage increased from 43.65% in 2005-06 to 62.46% in 2015-16. Overall, full immunization coverage in both 2005-06 and 2015-16 in all states was lowest in children from poorer households and improved with increasing socioeconomic status. The national concentration index decreased from 0.36 to 0.13 between the two study periods, indicating a reduction in poor-rich inequality. Similar reductions were observed for most states, except in states where inequalities were already minimal (i.e., Tamil Nadu) and in some northeastern states (i.e., Meghalaya and Manipur). In 2005-06, the contributors to wealth-related full immunization inequality were antenatal care, maternal education, and socioeconomic status. The same factors contributed to full immunization inequality in 2015-16 in addition to difficulty reaching a health facility. CONCLUSIONS: Immunization coverage and wealth-related equality have improved nationally and in most states over the last decade in India. Targeted, context-specific interventions could help address overall wealth-related full immunization inequalities. Intensified government efforts could help in this regard, particularly in high-focus states where child mortality remains high.

Identifying core competencies for practicing public health professionals: results from a Delphi exercise in Uttar Pradesh, India.

BACKGROUND: Ensuring the current public health workforce has appropriate competencies to fulfill essential public health functions is challenging in many low- and middle-income countries. The absence of an agreed set of core competencies to provide a basis for developing and assessing knowledge, skills, abilities, and attitudes contributes to this challenge. This study aims to identify the requisite core competencies for practicing health professionals in mid-level supervisory and program management roles to effectively perform their public health responsibilities in the resource-poor setting of Uttar Pradesh (UP), India. METHODS: We used a multi-step, interactive Delphi technique to develop an agreed set of public health competencies. A narrative review of core competency frameworks and key informant interviews with human resources for health experts in India were conducted to prepare an initial list of 40 competency statements in eight domains. We then organized a day-long workshop with 22 Indian public health experts and government officials, who added to and modified the initial list. A revised list of 54 competency statements was rated on a 5-point Likert scale. Aggregate statement scores were shared with the participants, who discussed the findings. Finally, the revised list was returned to participants for an additional round of ratings. The Wilcoxon matched-pairs signed-rank test was used to identify stability between steps, and consensus was defined using the percent agreement criterion. RESULTS: Stability between the first and second Delphi scoring steps was reached in 46 of the 54 statements. By the end of the second Delphi scoring step, consensus was reached on 48 competency statements across eight domains: public health sciences, assessment and analysis, policy and program management, financial management and budgeting, partnerships and collaboration, social and cultural determinants, communication, and leadership. CONCLUSIONS: This study produced a consensus set of core competencies and domains in public health that can be used to assess competencies of public health professionals and revise or develop new training programs to address desired competencies. Findings can also be used to support workforce development by informing competency-based job descriptions for recruitment and performance management in the Indian context, and potentially can be adapted for use in resource-poor settings globally.

Nasopharyngeal carriage of Streptococcus pneumoniae serotypes among children in India prior to the introduction of pneumococcal conjugate vaccines: a cross-sectional study.

BACKGROUND: Streptococcus pneumoniae is a major cause of pneumonia, meningitis, and other serious infections among children in India. India introduced the 13-valent pneumococcal conjugate vaccine (PCV) in several states in 2017, and is expected to expand to nationwide coverage in the near future. To establish a baseline for measuring the impact of PCV in India, we assessed overall and serotype-specific nasopharyngeal carriage in two pediatric populations. METHODS: A cross-sectional study was conducted in Palwal District, Haryana, from December 2016 to July 2017, prior to vaccine introduction. Children 2-59 months of age with clinical pneumonia seeking healthcare and those in the community with no clear illness were targeted for enrollment. A nasopharyngeal swab was collected and tested for pneumococcus using conventional culture and sequential multiplex PCR. Isolates were tested for antimicrobial resistance using an E test. Children were considered colonized if pneumococcus was isolated by culture or PCR. The prevalence of pneumococcal and serotype-specific colonization was compared between groups of children using log-binomial regression. RESULTS: Among 601 children enrolled, 91 had clinical pneumonia and 510 were community children. The proportion colonized with S. pneumoniae was 74.7 and 54.5% among children with clinical pneumonia and community children, respectively (adjusted prevalence ratio: 1.38; 95% confidence interval: 1.19, 1.60). The prevalence of PCV13 vaccine-type colonization was similar between children with clinical pneumonia (31.9%) and community children (28.0%; p = 0.46). The most common colonizing serotypes were 6A, 6B, 14, 19A, 19F, and 23F, all of which are included in the PCV13 vaccine product. Antimicrobial resistance to at least one drug was similar between isolates from children with clinical pneumonia (66.1%) and community children (61.5%; p = 0.49); while resistance to at least two drugs was more common among isolates from children with clinical pneumonia (25.8% vs. 16.4%; p = 0.08). Resistance for all drugs was consistently higher for PCV13 vaccine-type serotypes compared to non-vaccine serotypes in both groups. CONCLUSION: This study provides baseline information on the prevalence of serotype-specific pneumococcal colonization among children prior to the introduction of PCV in India. Our results suggest a role for pneumococcal vaccines in reducing pneumococcal colonization and antimicrobial resistant isolates circulating in India.

Socioeconomic and Demographic Effects on SARS-CoV-2 Testing: Evidence From the State of Uttar Pradesh, India.

Background The rapid global spread of SARS-CoV-2 highlighted critical challenges in healthcare systems worldwide, with differences in testing access and utilization becoming particularly evident. This study investigates the socioeconomic and demographic factors influencing SARS-CoV-2 testing service access and utilization during the second wave of the pandemic in Uttar Pradesh (UP), India. Methods The study was conducted from July to October 2023 in two districts of Uttar Pradesh (UP). These districts were chosen because one had the highest and the other the lowest SARS-CoV-2 testing rates per million population as reported from March to June 2021. The study population included consenting adult individuals with self-reported symptoms indicative of SARS-CoV-2 infection during March-June 2021. The study excluded individuals under 18 years, those who did not consent, pregnant or lactating mothers, and those with communication-impairing medical conditions. Data were collected using a structured questionnaire based on Andersen's Behavioural Model of Health Services Use. We used chi-squared tests for all categorical variables to obtain p-values and Poisson regression to identify factors influencing testing rates. Results We screened 4,595 individuals and identified 675 eligible participants for this study. Adjusted prevalence ratios derived from multiple variate Poisson regression models showed that participants in Sitapur had a 0.47 (95% CI: 0.39-0.57) times the prevalence of being tested than those in Lucknow. Furthermore, individuals from other backward castes and scheduled castes had a 1.15 (95% CI: 0.99-1.34) and 1.22 (95% CI: 0.95-1.56) times prevalence of being tested for SARS-CoV-2, respectively, when compared to the general caste population. Scheduled Tribes showed a higher prevalence of being tested, contrasting with existing literature. Households with low, middle, and high income showed a 1.46 (95% CI: 1.12-1.89), 1.52 (95% CI: 1.14-2.02), and 1.73 (95% CI: 1.23-2.45) times the prevalence of SARS-CoV-2 testing compared to those below the poverty line, respectively. Behavioral factors such as media use showed an inverse relationship with testing prevalence; individuals who did not watch TV at all had a 0.83 (95% CI: 0.70-0.99) times prevalence of being tested compared to frequent viewers, and similarly, those not using the internet on mobiles had a 0.82 (95% CI: 0.67-0.99) times prevalence than daily users. Individuals using private healthcare facilities had a 0.87 (95% CI: 0.77-0.99) times prevalence of SARS-CoV-2 testing compared to those using government facilities. Conclusions These findings highlight the importance of public health strategies that address socio-economic and behavioral disparities to ensure equitable testing access across all community groups.

Beyond "business as usual": lessons from FIFA for fair benefit-sharing in global health.

While researchers and agencies from low- and middle-income countries often contribute significantly to public health surveillance data, which is crucial for effective pandemic prevention, preparedness, and response activities, they often do not receive adequate compensation for their contributions. Incentivizing data sharing is important for informing public health responses to pathogens with pandemic potential. However, existing data-sharing legal frameworks have limitations. In this context, we looked beyond "business as usual" candidates to explore the applicability of a benefit-sharing model developed and implemented by the Fédération Internationale de Football Association (International Federation of Association Football; FIFA) in international association football. This model rewards grassroots contributions and redistributes benefits, promoting a fair balance of interests across diverse economic contexts. We discuss adapting FIFA's mechanisms, including training compensation and solidarity payments, to create a novel benefit-sharing framework in global health. Given the complexity of global health, we note ways in which components of the FIFA model would need to be adapted for global health. Challenges such as integrating into existing legal frameworks, ensuring broad international buy-in, and accommodating different pandemic periods are examined. While adapting the FIFA model presents challenges, it offers a promising approach to achieving more equitable data sharing and benefit distribution in global health.

Estimates of hospitalisations and deaths in patients with COVID-19 associated with undiagnosed diabetes during the first phase of the pandemic in eight low-income and middle-income countries: a modelling study.

Background: Patients with COVID-19 that had diagnosed chronic diseases - including diabetes - may experience higher rates of hospitalisation and mortality relative to the general population. However, the burden of undiagnosed co-morbidities during the pandemic has not been adequately studied. Methods: We developed a model to estimate the hospitalisation and mortality burden of patients with COVID-19 that had undiagnosed type 1 and type 2 diabetes (UD). The retrospective analytical modelling framework was informed by country-level demographic, epidemiological and COVID-19 data and parameters. Eight low-and middle-income countries (LMICs) were studied: Brazil, China, India, Indonesia, Mexico, Nigeria, Pakistan, and South Africa. The modelling period consisted of the first phase of the pandemic - starting from the date when a country identified its first COVID case to the date when the country reached 1% coverage with one dose of a COVID-19 vaccine. The end date ranged from Jan 20, 2021 for China to June 2, 2021 for Nigeria. Additionally, we estimated the change in burden under a scenario in which all individuals with UD had been diagnosed prior to the pandemic. Findings: Based on our modelling estimates, across the eight countries, 6.7 (95% uncertainty interval: 3.4-11.3) million COVID-19 hospitalised patients had UD of which 1.9 (0.9-3.4) million died. These represented 21.1% (13.4%-30.1%) of all COVID-19 hospitalisations and 30.5% (14.3%-55.5%) of all COVID-19 deaths in these countries. Based on modelling estimates, if these populations had been diagnosed for diabetes prior to the COVID-19 pandemic, 1.7% (-3.0% to 5.9%) of COVID-19 hospitalisations and 5.0% (-0.9% to 14.1%) of COVID-19 deaths could have been prevented, and 1.8 (-0.3 to 5.0) million quality-adjusted life years gained. Interpretation: Our findings suggest that undiagnosed diabetes contributed substantially to COVID-19 hospitalisations and deaths in many LMICs. Funding: This work was supported, in part, by the Bill & Melinda Gates Foundation [INV-029062] and FIND.

Effect of hybrid immunity, school reopening, and the Omicron variant on the trajectory of the COVID-19 epidemic in India: a modelling study.

Background: The course of the COVID-19 pandemic has been driven by several dynamic behavioral, immunological, and viral factors. We used mathematical modeling to explore how the concurrent reopening of schools, increasing levels of hybrid immunity, and the emergence of the Omicron variant affected the trajectory of the pandemic in India, using Andhra Pradesh (pop: 53 million) as an exemplar Indian state. Methods: We constructed an age- and contact-structured compartmental model that allows for individuals to proceed through various states depending on whether they have received zero, one, or two doses of the COVID-19 vaccine. We calibrated our model using results from another model (i.e., INDSCI-SIM) as well as available context-specific serosurvey data. The introduction of the Omicron variant is modelled alongside protection gained from hybrid immunity. We predict disease dynamics in the background of hybrid immunity coming from infections and an ongoing vaccination program, given prior levels of seropositivity from earlier waves of infection. We describe the consequences of school reopening on cases across different age-bands, as well as the impact of the Omicron (BA.2) variant. Findings: We show the existence of an epidemic peak in India that is strongly related to the value of background seroprevalence. As expected, because children were not vaccinated in India, re-opening schools increases the number of cases in children more than in adults, although in all scenarios, the peak number of active hospitalizations was never greater than 0.45 times the corresponding peak in the Delta wave before schools were reopened. We varied the level of infection induced seropositivity in our model and found the height of the peak associated with schools reopening reduced as background infection-induced seropositivity increased from 20% to 40%. At reported values of seropositivity of 64% from representative surveys done in India, no discernible peak was observed. We also explored counterfactual scenarios regarding the effect of vaccination on hybrid immunity. We found that in the absence of vaccination, even at high levels of seroprevalence (>60%), the emergence of the Omicron variant would have resulted in a large rise in cases across all age bands by as much as 1.8 times. We conclude that the presence of high levels of hybrid immunity resulted in fewer cases in the Omicron wave than in the Delta wave. Interpretation: In India, decreasing prevalence of immunologically naïve individuals of all ages was associated with fewer cases reported once schools were reopened. In addition, hybrid immunity, together with the lower intrinsic severity of disease associated with the Omicron variant, contributed to low reported COVID-19 hospitalizations and deaths. Funding: World Health Organization, Mphasis.

Estimating national, regional and provincial cost-effectiveness of introducing childhood 13-valent pneumococcal conjugate vaccination in China: a modelling analysis.

Background: Although 13-valent pneumococcal conjugate vaccine (PCV13) is available in China's private market, it has yet to be introduced into the National Immunization Programme (NIP) and is therefore not available to large parts of the population. This study aimed to estimate the cost-effectiveness of including PCV13 in China's NIP at national and provincial levels. Methods: We adopted a decision-tree Markov model to estimate the cost-effectiveness of adding 3-dose PCV13 in the NIP compared to the status quo in the private market from a societal perspective. The model hypothesized a birth cohort for five years after vaccine introduction. Treatment costs and vaccine program costs were calculated from Chinese Center for Disease Control and Prevention (CDC) and national insurance databases. Disease burden data, incidence rate ratios, and other parameters were derived from published and grey literature. Cases and deaths averted, quality-adjusted life years (QALYs) gained, and incremental cost-effectiveness ratios (ICERs) were estimated at the provincial, regional, and national levels. One-way, scenario and probabilistic sensitivity analyses were conducted to explore model uncertainty. Findings: At the national level, introducing PCV13 in the NIP was predicted to prevent approximately 4807 pneumococcal deaths (66% reduction) and 1,057,650 pneumococcal cases (17% reduction) in the first five years of the 2019 birth cohort. Under the assumed base case price of US$ 25 per dose in the NIP, PCV13 in the NIP was cost-effective nationally with ICER of US$ 5.222 per QALY gained, and was cost-effective in 17 and cost-saving in 4 of the 31 provinces compared to the status quo. One-way and scenario sensitivity analyses indicated robust results when varying all model parameters, and probabilistic sensitivity analysis showed a 98% probability of cost-effectiveness nationally. Interpretation: Our findings highlight the cost-effectiveness of introducing PCV13 in China's NIP. Provincial results supported subnational introduction of PCV13, and priority should be given to less socioeconomically developed provinces. Since vaccination cost is the most influential model parameter, efforts to improve PCV affordability after pooled procurement will benefit public health in a cost-effective manner. Funding: The Bill & Melinda Gates Foundation.

Neonatal, Infant, and Child Mortality in India: Progress and Future Directions.

In India, considerable progress has been made in reducing child mortality rates. Despite this achievement, wide disparities persist across and socio-economic strata, and persistent challenges, such as malnutrition, poor sanitation, and lack of clean water. This paper provides a comprehensive review of the state of child health in India, examining key risk factors and causes of child mortality, assessing the coverage of child health interventions, and highlighting critical public health programs and policies. The authors also discuss future directions and recommendations for bolstering ongoing efforts to improve child health. These include state- and region-specific interventions, prioritizing social determinants of health, strengthening data systems, leveraging existing programs like the National Health Mission (NHM) and Ayushman Bharat Pradhan Mantri Jan Arogya Yojana (PM-JAY), and the proposed Public Health Management Cadre (PHMC). The authors argue that reducing child mortality requires not only scaled-up interventions but a comprehensive approach that addresses all dimensions of health, from social determinants to system strengthening.

Accelerating access for all through research and innovation in immunization: Recommendations from Strategic Priority 7 of the Immunization Agenda 2030.

Research and innovation have been fundamental to many of the successes in immunization thus far, and will play important roles in the future success of Immunization Agenda 2030 (IA2030). Strategic Priority 7 (SP7) of IA2030, which addresses research and innovation, is explicitly informed by country needs and priorities, and aims to strengthen the innovation ecosystem through capacity building and collaboration at country, regional, and global levels. SP7 identifies four key focus areas: (1) "needs-based innovation", (2) "new and improved products, services, and practices", (3) "evidence for implementation", and (4) "local capacity". Strategic interventions in these key focus areas apply the lessons of the Global Vaccine Action Plan and the "Decade of Vaccines" to emphasize local innovation, promote the use of research by countries to improve program performance and impact, and encourage capacity building for the development and implementation of innovations. The proposed approach will maintain a focus on the development of new vaccines and the improvement of existing vaccines, and increase attention to innovation in service delivery. Monitoring and evaluation will foster evidence-based priority setting at the country level and help to ground the global research and development (R&D) agenda in the needs of communities. Together, these approaches are intended to harness the power of research and innovation more effectively, to meet the challenges of the future and achieve the ambitious goals of IA2030.

Understanding determinants of vaccine hesitancy and acceptance in India: A qualitative study of government officials and civil society stakeholders.

INTRODUCTION: Few studies have described the drivers of vaccine hesitancy and acceptance in India from the perspective of those involved in the design and implementation of vaccine campaigns-such as government officials and civil society stakeholders-a prerequisite to developing approaches to address this barrier to high immunization coverage and further child health improvements. METHODS: We conducted a qualitative study to understand government officials and civil society stakeholders' perceptions of the drivers of vaccine hesitancy in India. We conducted in-depth phone interviews using a structured guide of open-ended questions with 21 participants from international and national non-governmental organizations, professional associations, and universities, and state and national government-six national-level stakeholders in New Delhi, six state-level stakeholders in Uttar Pradesh, six in Kerala, and three in Gujarat-from July 2020 to October 2020. We analyzed data through a multi-stage process following Grounded Theory. We present findings on individual-level, contextual, and vaccine/vaccination program-specific factors influencing vaccine hesitancy. RESULTS: We identified multiple drivers and complex ways they influence vaccine beliefs, attitudes, and behaviors from the perspective of government officials and civil society stakeholders involved in vaccine campaigns. Important individual-level influences were low awareness of the benefits of vaccination, safety concerns, especially related to mild adverse events following immunization, and mistrust in government and health service quality. Contextual-level factors included communications, the media environment, and social media, which serves as a major conduit of misinformation and driver of hesitancy, as well as sociodemographic factors-specific drivers varied widely by income, education, urban/rural setting, and across religious and cultural groups. Among vaccine/vaccination-level issues, vaccine program design and delivery and the role of health care professionals emerged as the strongest determinants of hesitancy. CONCLUSIONS: Drivers of vaccine hesitancy in India, as elsewhere, vary widely by local context; successful interventions should address individual, contextual, and vaccine-specific factors. While previous studies focused on individual-level factors, our study demonstrates the equal importance of contextual and vaccine-specific influences, especially the communication and media environment, influential leaders, sociodemographic factors, and frontline health workers.

All-cause mortality during the COVID-19 pandemic in Chennai, India: an observational study.

BACKGROUND: India has been severely affected by the ongoing COVID-19 pandemic. However, due to shortcomings in disease surveillance, the burden of mortality associated with COVID-19 remains poorly understood. We aimed to assess changes in mortality during the pandemic in Chennai, Tamil Nadu, using data on all-cause mortality within the district. METHODS: For this observational study, we analysed comprehensive death registrations in Chennai, from Jan 1, 2016, to June 30, 2021. We estimated expected mortality without the effects of the COVID-19 pandemic by fitting models to observed mortality time series during the pre-pandemic period, with stratification by age and sex. Additionally, we considered three periods of interest: the first 4 weeks of India's first lockdown (March 24 to April 20, 2020), the 4-month period including the first wave of the pandemic in Chennai (May 1 to Aug 31, 2020), and the 4-month period including the second wave of the pandemic in Chennai (March 1 to June 30, 2021). We computed the difference between observed and expected mortality from March 1, 2020, to June 30, 2021, and compared pandemic-associated mortality across socioeconomically distinct communities (measured with use of 2011 census of India data) with regression analyses. FINDINGS: Between March 1, 2020, and June 30, 2021, 87 870 deaths were registered in areas of Chennai district represented by the 2011 census, exceeding expected deaths by 25 990 (95% uncertainty interval 25 640-26 360) or 5·18 (5·11-5·25) excess deaths per 1000 people. Stratified by age, excess deaths numbered 21·02 (20·54-21·49) excess deaths per 1000 people for individuals aged 60-69 years, 39·74 (38·73-40·69) for those aged 70-79 years, and 96·90 (93·35-100·16) for those aged 80 years or older. Neighbourhoods with lower socioeconomic status had 0·7% to 2·8% increases in pandemic-associated mortality per 1 SD increase in each measure of community disadvantage, due largely to a disproportionate increase in mortality within these neighbourhoods during the second wave. Conversely, differences in excess mortality across communities were not clearly associated with socioeconomic status measures during the first wave. For each increase by 1 SD in measures of community disadvantage, neighbourhoods had 3·6% to 8·6% lower pandemic-associated mortality during the first 4 weeks of India's country-wide lockdown, before widespread SARS-CoV-2 circulation was underway in Chennai. The greatest reductions in mortality during this early lockdown period were observed among men aged 20-29 years, with 58% (54-62) fewer deaths than expected from pre-pandemic trends. INTERPRETATION: Mortality in Chennai increased substantially but heterogeneously during the COVID-19 pandemic, with the greatest burden concentrated in disadvantaged communities. Reported COVID-19 deaths greatly underestimated pandemic-associated mortality. FUNDING: National Institute of General Medical Sciences, Bill & Melinda Gates Foundation, National Science Foundation. TRANSLATION: For the Hindi translation of the abstract see Supplementary Materials section.

Continuous positive airway pressure for children in resource-limited settings, effect on mortality and adverse events: systematic review and meta-analysis.

OBJECTIVE: Determine non-invasive ventilation with continuous positive airway pressure (CPAP) outcomes for paediatric respiratory distress in low-income and middle-income countries (LMICs). DESIGN: Systematic review and meta-analysis. SETTING: LMIC hospitals. PATIENTS: One month to 15 year olds with respiratory distress. INTERVENTIONS: We searched Medline, Embase, LILACS, Web of Science and Scopus on 7 April 2020. Included studies assessed CPAP safety, efficacy or effectiveness. All study types were included; neonatal only studies were excluded. Data were extracted by two reviewers and bias was assessed. Certainty of evidence was evaluated, and risk ratios (RR) were produced for meta-analyses. (PROSPERO protocol CRD42018084278). RESULTS: 2174 papers were screened, 20 were included in the systematic review and 3 were included in two separate meta-analyses of mortality and adverse events. Studies suitable for meta-analysis were randomised controlled trials (RCTs) from Bangladesh, Ghana and Malawi. For meta-analyses comparing death or adverse events between CPAP and low-flow oxygen recipients, we found no clear CPAP effect on mortality (RR 0.75, 95% CI 0.33 to 1.72) or adverse events (RR 1.52, CI 0.71 to 3.26). We downgraded the certainty of evidence for both death and adverse events outcomes to 'low' due to design issues and results discrepancies across RCTs. CONCLUSIONS: Evidence for CPAP efficacy against mortality and adverse events has low certainty and is context dependent. Hospitals introducing CPAP need to have mechanisms in place to optimise safety in the context it is being used; this includes the location (a high dependency or intensive care area), adequate numbers of staff trained in CPAP use, close monitoring and mechanisms for escalation, daily direct physician supervision, equipment that is age appropriate and user-friendly and continuous monitoring of outcomes and quality of care.

National, regional, and provincial disease burden attributed to Streptococcus pneumoniae and Haemophilus influenzae type b in children in China: Modelled estimates for 2010-17.

Background: Vaccination against Streptococcus pneumoniae (pneumococcus) and Haemophilus influenzae type b (Hib) is not included in China's national immunization programme. To inform China's immunization polices, we estimated annual national, regional, and provincial childhood mortality and morbidity attributable to pneumococcus and Hib in 2010-17. Methods: We estimated proportions of pneumonia and meningitis deaths and cases attributable to pneumococcus and Hib using evidence from vaccine clinical trials and surveillance studies of bacterial meningitis and pathogen-specific case fatality ratios (CFR). Then we applied the proportions to model provincial-level pneumonia cases and deaths, meningitis deaths and meningitis CFR in children aged 1-59 months, accounting for vaccine coverage. Non-pneumonia, non-meningitis (NPNM) invasive disease cases were derived by applying NPNM meningitis ratios to meningitis estimates. Findings: In 2010-17, annual pneumococcal deaths fell by 49% from 15 600 (uncertainty range: 10 800-17 300) to 8 000 (5 500-8 900), and Hib deaths fell by 56% from 6 500 (4 500-8 800) to 2 900 (2 000-3 900). Severe pneumococcal and Hib cases decreased by 16% to 218 200 (161 500-252 200) in 2017 and 29% to 49 900 (29 000-99 100). Estimated 2017 national three-dose coverage in private market was 1·3% for PCV and 33·4% for Hib vaccine among children aged 1-59 months. Provinces in the west region had the highest disease burden. Interpretation: Childhood mortality and morbidity attributable to pneumococcal and Hib has decreased in China, but still substantially varied by region and province. Higher vaccine coverage could further reduce disease burden. Funding: Bill & Melinda Gates Foundation.

Immunization programs to support primary health care and achieve universal health coverage.

Gains in immunization coverage and delivery of primary health care service have stagnated in recent years. Remaining gaps in service coverage reflect multiple underlying reasons that may be amenable to improved health system design. Immunization systems and other primary health care services can be mutually supportive, for improved service delivery and for strengthening of Universal Health Coverage. Improvements require that dynamic and multi-faceted barriers and risks be addressed. These include workforce availability, quality data systems and use, leadership and management that is innovative, flexible, data driven and responsive to local needs. Concurrently, improvements in procurement, supply chain, logistics and delivery systems, and integrated monitoring of vaccine coverage and epidemiological disease surveillance with laboratory systems, and vaccine safety will be needed to support community engagement and drive prioritized actions and communication. Finally, political will and sustained resource commitment with transparent accountability mechanisms are required. The experience of the impact of COVID-19 pandemic on essential PHC services and the challenges of vaccine roll-out affords an opportunity to apply lessons learned in order to enhance vaccine services integrated with strong primary health care services and universal health coverage across the life course.