Reduced Odds of Severe Acute Respiratory Syndrome Coronavirus 2 Reinfection After Vaccination Among New York City Adults, July 2021-November 2021.

BACKGROUND: Belief that vaccination is not needed for individuals with prior infection contributes to coronavirus disease 2019 (COVID-19) vaccine hesitancy. Among individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) before vaccines became available, we determined whether vaccinated individuals had reduced odds of reinfection. METHODS: We conducted a case-control study among adult New York City residents who tested positive for SARS-CoV-2 infection in 2020 and had not died or tested positive again >90 days after an initial positive test as of 1 July 2021. Case patients with reinfection during July 2021-November 2021 and controls with no reinfection were matched (1:3) on age, sex, timing of initial positive test in 2020, and neighborhood poverty level. Matched odds ratios (mORs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression. RESULTS: Of 349 827 eligible adults, 2583 were reinfected during July 2021-November 2021. Of 2401 with complete matching criteria data, 1102 (45.9%) were known to be symptomatic for COVID-19-like illness, and 96 (4.0%) were hospitalized. Unvaccinated individuals, compared with individuals fully vaccinated within the prior 90 days, had elevated odds of reinfection (mOR, 3.21; 95% CI, 2.70 to 3.82), of symptomatic reinfection (mOR, 2.97; 95% CI, 2.31 to 3.83), and of reinfection with hospitalization (mOR, 2.09; 95% CI, .91 to 4.79). CONCLUSIONS: Vaccination reduced odds of reinfections when the Delta variant predominated. Further studies should assess risk of severe outcomes among reinfected persons as new variants emerge, infection- and vaccine-induced immunity wanes, and booster doses are administered.

Effects of Return-to-Office, Public Schools Reopening, and Vaccination Mandates on COVID-19 Cases Among Municipal Employee Residents of New York City.

OBJECTIVE: On September 13, 2021, teleworking ended for New York City municipal employees, and Department of Education employees returned to reopened schools. On October 29, COVID-19 vaccination was mandated. We assessed these mandates' short-term effects on disease transmission. METHODS: Using difference-in-difference analyses, we calculated COVID-19 incidence rate ratios (IRRs) among residents 18 to 64 years old by employment status before and after policy implementation. RESULTS: IRRs after (September 23-October 28) versus before (July 5-September 12) the return-to-office mandate were similar between office-based City employees and non-City employees. Among Department of Education employees, the IRR after schools reopened was elevated by 28.4% (95% confidence interval, 17.3%-40.3%). Among City employees, the IRR after (October 29-November 30) versus before (September 23-October 28) the vaccination mandate was lowered by 20.1% (95% confidence interval, 13.7%-26.0%). CONCLUSIONS: Workforce mandates influenced disease transmission, among other societal effects.

Susceptible windows of exposure to fine particulate matter and fetal growth trajectories in the Spanish INMA (INfancia y Medio Ambiente) birth cohort.

While prior studies report associations between fine particulate matter (PM2.5) exposure and fetal growth, few have explored temporally refined susceptible windows of exposure. We included 2328 women from the Spanish INMA Project from 2003 to 2008. Longitudinal growth curves were constructed for each fetus using ultrasounds from 12, 20, and 34 gestational weeks. Z-scores representing growth trajectories of biparietal diameter, femur length, abdominal circumference (AC), and estimated fetal weight (EFW) during early (0-12 weeks), mid- (12-20 weeks), and late (20-34 weeks) pregnancy were calculated. A spatio-temporal random forest model with back-extrapolation provided weekly PM2.5 exposure estimates for each woman during her pregnancy. Distributed lag non-linear models were implemented within the Bayesian hierarchical framework to identify susceptible windows of exposure for each outcome and cumulative effects [ßcum, 95% credible interval (CrI)] were aggregated across adjacent weeks. For comparison, general linear models evaluated associations between PM2.5 averaged across multi-week periods (i.e., weeks 1-11, 12-19, and 20-33) and fetal growth, mutually adjusted for exposure during each period. Results are presented as %change in z-scores per 5 µg/m3 in PM2.5, adjusted for covariates. Weeks 1-6 [ßcum = -0.77%, 95%CrI (-1.07%, -0.47%)] were identified as a susceptible window of exposure for reduced late pregnancy EFW while weeks 29-33 were positively associated with this outcome [ßcum = 0.42%, 95%CrI (0.20%, 0.64%)]. A similar pattern was observed for AC in late pregnancy. In linear regression models, PM2.5 exposure averaged across weeks 1-11 was associated with reduced late pregnancy EFW and AC; but, positive associations between PM2.5 and EFW or AC trajectories in late pregnancy were not observed. PM2.5 exposures during specific weeks may affect fetal growth differentially across pregnancy and such associations may be missed by averaging exposure across multi-week periods, highlighting the importance of temporally refined exposure estimates when studying the associations of air pollution with fetal growth.

Comparative hospitalization risk for SARS-CoV-2 Omicron and Delta variant infections, by variant predominance periods and patient-level sequencing results, New York City, August 2021-January 2022.

BACKGROUND: Comparing disease severity between SARS-CoV-2 variants among populations with varied vaccination and infection histories can help characterize emerging variants and support healthcare system preparedness. METHODS: We compared COVID-19 hospitalization risk among New York City residents with positive laboratory-based SARS-CoV-2 tests when ≥98% of sequencing results were Delta (August-November 2021) or Omicron (BA.1 and sublineages, January 2022). A secondary analysis defined variant exposure using patient-level sequencing results during July 2021-January 2022, comprising 1-18% of weekly confirmed cases. RESULTS: Hospitalization risk was lower among patients testing positive when Omicron (16,025/488,053, 3.3%) than when Delta predominated (8268/158,799, 5.2%). In multivariable analysis adjusting for demographic characteristics and prior diagnosis and vaccination status, patients testing positive when Omicron predominated, compared with Delta, had 0.72 (95% CI: 0.63, 0.82) times the hospitalization risk. In a secondary analysis of patients with sequencing results, hospitalization risk was similar among patients infected with Omicron (2042/29,866, 6.8%), compared with Delta (1780/25,272, 7.0%), and higher among the subset who received two mRNA vaccine doses (adjusted relative risk 1.64; 95% CI: 1.44, 1.87). CONCLUSIONS: Hospitalization risk was lower among patients testing positive when Omicron predominated, compared with Delta. This finding persisted after adjusting for prior diagnosis and vaccination status, suggesting intrinsic virologic properties, not population-based immunity, explained the lower severity. Secondary analyses demonstrated collider bias from the sequencing sampling frame changing over time in ways associated with disease severity. Representative data collection is necessary to avoid bias when comparing disease severity between previously dominant and newly emerging variants.

Case growth analysis to inform local response to COVID-19 epidemic in a diverse U.S community.

Early detection of new outbreak waves is critical for effective and sustained response to the COVID-19 pandemic. We conducted a growth rate analysis using local community and inpatient records from seven hospital systems to characterize distinct phases in SARS-CoV-2 outbreak waves in the Greater Houston area. We determined the transition times from rapid spread of infection in the community to surge in the number of inpatients in local hospitals. We identified 193,237 residents who tested positive for SARS-CoV-2 via molecular testing from April 8, 2020 to June 30, 2021, and 30,031 residents admitted within local healthcare institutions with a positive SARS-CoV-2 test, including emergency cases. We detected two distinct COVID-19 waves: May 12, 2020-September 6, 2020 and September 27, 2020-May 15, 2021; each encompassed four growth phases: lagging, exponential/rapid growth, deceleration, and stationary/linear. Our findings showed that, during early stages of the pandemic, the surge in the number of daily cases in the community preceded that of inpatients admitted to local hospitals by 12-36 days. Rapid decline in hospitalized cases was an early indicator of transition to deceleration in the community. Our real-time analysis informed local pandemic response in one of the largest U.S. metropolitan areas, providing an operationalized framework to support robust real-world surveillance for outbreak preparedness.

Trends and Correlates of Breakthrough Infections With SARS-CoV-2.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant has been hypothesized to decrease the efficacy of COVID-19 vaccines. Factors associated with infections with SARS-CoV-2 after vaccination are unknown. In this observational cohort study, we examined two groups in Harris County, Texas: (1) individuals with positive Nucleic Acid Amplification test between 12/14/2020 and 9/30/2021 and (2) the subset of individuals fully vaccinated in the same time period. Infected individuals were classified as a breakthrough if their infection occurred 14 days after their vaccination had been completed. Among fully vaccinated individuals, demographic and vaccine factors associated with breakthrough infections were assessed. Of 146,731 positive SARS-CoV-2 tests, 7.5% were breakthrough infections. Correlates of breakthrough infection included young adult age, female, White race, and receiving the Janssen vaccine, after adjustments including the amount of community spread at the time of infection. Vaccines remained effective in decreasing the probability of testing positive for SARS-CoV-2. The data indicate that increased vaccine booster uptake would help decrease new infections.

Identifying Sensitive Windows of Exposure to NO2 and Fetal Growth Trajectories in a Spanish Birth Cohort.

BACKGROUND: We previously identified associations between trimester-specific NO2 exposures and reduced fetal growth in the Spanish INfancia y Medio Ambiente (INMA) project. Here, we use temporally refined exposure estimates to explore the impact of narrow (weekly) windows of exposure on fetal growth. METHODS: We included 1,685 women from INMA with serial ultrasounds at 12, 20, and 34 gestational weeks. We measured biparietal diameter (BPD), femur length, and abdominal circumference (AC) and from them calculated estimated fetal weight (EFW). We calculated z-scores describing trajectories of each parameter during early (0-12 weeks), mid (12-20 weeks), and late (20-34 weeks) pregnancy, based on longitudinal growth curves from mixed-effects models. We estimated weekly NO2 exposures at each woman's residence using land-use regression models. We applied distributed lag nonlinear models to identify sensitive windows of exposure. We present effect estimates as the percentage change in fetal growth per 10 µg/m3 increase in NO2 exposure, and we calculated cumulative effect estimates by aggregating estimates across adjacent lags. RESULTS: We identified weeks 5-12 as a sensitive window for NO2 exposure on late EFW (cumulative ß = -3.0%; 95% CI = -4.1%, -1.9%). We identified weeks 6-19 as a sensitive window for late growth in BPD (cumulative ß = -2.0%; 95% CI = -2.7%, -1.4%) and weeks 8-13 for AC (cumulative ß = -0.68%; 95% CI = -0.97%, -0.40%). We found suggestive evidence that third trimester NO2 exposure is associated with increased AC, BPD, and EFW growth in late pregnancy. CONCLUSIONS: Our findings are consistent with the hypothesis that NO2 exposure is associated with alterations in growth of EFW, BPD, and AC dependent on the specific timing of exposure during gestation.

Reduced COVID-19 hospitalizations among New York City residents following age-based SARS-CoV-2 vaccine eligibility: Evidence from a regression discontinuity design.

BACKGROUND: In clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when ≥ 65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not. METHODS: We constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths. RESULTS: Hospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10). CONCLUSION: The vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible ≥ 65-year-old population by approximately 15% in the first eight weeks. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.

Examining Social Vulnerability and the Association With COVID-19 Incidence in Harris County, Texas.

Studies have investigated the association between social vulnerability and SARS-CoV-2 incidence. However, few studies have examined small geographic units such as census tracts, examined geographic regions with large numbers of Hispanic and Black populations, controlled for testing rates, and incorporated stay-at-home measures into their analyses. Understanding the relationship between social vulnerability and SARS-CoV-2 incidence is critical to understanding the interplay between social determinants and implementing risk mitigation guidelines to curtail the spread of infectious diseases. The objective of this study was to examine the relationship between CDC's Social Vulnerability Index (SVI) and SARS-CoV-2 incidence while controlling for testing rates and the proportion of those who stayed completely at home among 783 Harris County, Texas census tracts. SARS-CoV-2 incidence data were collected between May 15 and October 1, 2020. The SVI and its themes were the primary exposures. Median percent time at home was used as a covariate to measure the effect of staying at home on the association between social vulnerability and SARS-CoV-2 incidence. Data were analyzed using Kruskal Wallis and negative binomial regressions (NBR) controlling for testing rates and staying at home. Results showed that a unit increase in the SVI score and the SVI themes were associated with significant increases in SARS-CoV-2 incidence. The incidence risk ratio (IRR) was 1.090 (95% CI, 1.082, 1.098) for the overall SVI; 1.107 (95% CI, 1.098, 1.115) for minority status/language; 1.090 (95% CI, 1.083, 1.098) for socioeconomic; 1.060 (95% CI, 1.050, 1.071) for household composition/disability, and 1.057 (95% CI, 1.047, 1.066) for housing type/transportation. When controlling for stay-at-home, the association between SVI themes and SARS-CoV-2 incidence remained significant. In the NBR model that included all four SVI themes, only the socioeconomic and minority status/language themes remained significantly associated with SARS-CoV-2 incidence. Community-level infections were not explained by a communities' inability to stay at home. These findings suggest that community-level social vulnerability, such as socioeconomic status, language barriers, use of public transportation, and housing density may play a role in the risk of SARS-CoV-2 infection regardless of the ability of some communities to stay at home because of the need to work or other reasons.

Trends in mental health outcomes and combat exposure among US marines returning from Iraq, Afghanistan or other deployments, 2004-13.

BACKGROUND: As of 2015, more than 2.7 million US military Veterans have served in support of the Global War on Terror. The negative sequelae associated with deployment stressors and related traumas are well-documented. Although data on mental health issues are routinely collected from service members returning from deployment, these data have not been made publicly available, leaving researchers and clinicians to rely on convenience samples, outdated studies and small sample sizes. METHODS: Population-based data of US Marines returning from deployment between 2004 and 2013 were analyzed, using the Post-Deployment Health Assessment. RESULTS: Rates of Marines returning from Iraq who screened positive for depression ranged from 19.31 to 30.02%; suicidal ideation ranged from 0 to 1.44%. Marines screening positive for PTSD ranged from 3.00 to 12.41%; combat exposure ranged from 15.58 to 55.12%. Depression was indicated for between 12.54 and 30.04% of Marines returning from Afghanistan, while suicidal ideation ranged from 0 to 5.33%. PTSD percentages ranged from 6.64 to 18.18%; combat exposure ranged between 42.92 and 75%. CONCLUSION: Our results support the heterogeneity of experiences and mental health sequelae of service members returning from deployments. Outcomes for Afghanistan and Iraq Veterans fluctuate with changes in OPTEMPO across theaters over time.

Predictors of Posttraumatic Stress Disorder, Anxiety Disorders, Depressive Disorders, and Any Mental Health Condition Among U.S. Soldiers and Marines, 2001-2011.

Understanding mental health disorder diagnosis and treatment seeking among active-duty military personnel is a topic with both clinical and policy implications. It has been well documented in military populations that individual-level military experience, including deployment history and combat exposure, influences mental health outcomes, but the impact of unit-level factors is less well understood. In the current study, we used administrative longitudinal data to examine a comprehensive set of unit- and individual-level predictors of posttraumatic stress disorder (PTSD), non-PTSD anxiety disorders, depressive disorders, and overall mental health diagnoses among Army and Marines Corps personnel. Using Cox survival models for time-dependent variables, we analyzed time from military accession (between January 1, 2001 and December 31, 2011) until first mental health diagnosis for 773,359 soldiers and 332,093 Marines. Prior diagnosis of a substance abuse disorder during one's military career, hazard ratios (HRs) = 1.68-3.10, and cumulative time spent deployed, HRs = 1.11-2.04, were the most predictive risk factors for all outcomes. Male sex, HRs = 0.35-0.57, and officer rank, HRs = 0.13-0.23, were the most protective factors. Unit-level rate of high deployment stress was a small but significant predictor of all outcomes after controlling for individual-level deployment history and other predictors, HRs = 1.01-1.05. Findings suggest both unit- and individual-level risk and protective factors of mental health diagnoses associated with treatment seeking. Clinical, including mental health assessment and management, and policy implications related to the military environment and the individual as it relates to mental health disorders are discussed.

Evaluating and implementing temporal, spatial, and spatio-temporal methods for outbreak detection in a local syndromic surveillance system.

The New York City Department of Health and Mental Hygiene has operated an emergency department syndromic surveillance system since 2001, using temporal and spatial scan statistics run on a daily basis for cluster detection. Since the system was originally implemented, a number of new methods have been proposed for use in cluster detection. We evaluated six temporal and four spatial/spatio-temporal detection methods using syndromic surveillance data spiked with simulated injections. The algorithms were compared on several metrics, including sensitivity, specificity, positive predictive value, coherence, and timeliness. We also evaluated each method's implementation, programming time, run time, and the ease of use. Among the temporal methods, at a set specificity of 95%, a Holt-Winters exponential smoother performed the best, detecting 19% of the simulated injects across all shapes and sizes, followed by an autoregressive moving average model (16%), a generalized linear model (15%), a modified version of the Early Aberration Reporting System's C2 algorithm (13%), a temporal scan statistic (11%), and a cumulative sum control chart (<2%). Of the spatial/spatio-temporal methods we tested, a spatial scan statistic detected 3% of all injects, a Bayes regression found 2%, and a generalized linear mixed model and a space-time permutation scan statistic detected none at a specificity of 95%. Positive predictive value was low (<7%) for all methods. Overall, the detection methods we tested did not perform well in identifying the temporal and spatial clusters of cases in the inject dataset. The spatial scan statistic, our current method for spatial cluster detection, performed slightly better than the other tested methods across different inject magnitudes and types. Furthermore, we found the scan statistics, as applied in the SaTScan software package, to be the easiest to program and implement for daily data analysis.

Disparities in Reportable Communicable Disease Incidence by Census Tract-Level Poverty, New York City, 2006-2013.

OBJECTIVES: We described disparities in selected communicable disease incidence across area-based poverty levels in New York City, an area with more than 8 million residents and pronounced household income inequality. METHODS: We geocoded and categorized cases of 53 communicable diseases diagnosed during 2006 to 2013 by census tract-based poverty level. Age-standardized incidence rate ratios (IRRs) were calculated for areas with 30% or more versus fewer than 10% of residents below the federal poverty threshold. RESULTS: Diseases associated with high poverty included rickettsialpox (IRR = 3.69; 95% confidence interval [CI] = 2.29, 5.95), chronic hepatitis C (IRR for new reports = 3.58; 95% CI = 3.50, 3.66), and malaria (IRR = 3.48; 95% CI = 2.97, 4.08). Diseases associated with low poverty included domestic tick-borne diseases acquired through travel to areas where infected vectors are prevalent, such as human granulocytic anaplasmosis (IRR = 0.08; 95% CI = 0.03, 0.19) and Lyme disease (IRR = 0.34; 95% CI = 0.32, 0.36). CONCLUSIONS: Residents of high poverty areas were disproportionately affected by certain communicable diseases that are amenable to public health interventions. Future work should clarify subgroups at highest risk, identify reasons for the observed associations, and use findings to support programs to minimize disparities.

Building-level analyses to prospectively detect influenza outbreaks in long-term care facilities: New York City, 2013-2014.

BACKGROUND: Timely outbreak detection is necessary to successfully control influenza in long-term care facilities (LTCFs) and other institutions. To supplement nosocomial outbreak reports, calls from infection control staff, and active laboratory surveillance, the New York City (NYC) Department of Health and Mental Hygiene implemented an automated building-level analysis to proactively identify LTCFs with laboratory-confirmed influenza activity. METHODS: Geocoded addresses of LTCFs in NYC were compared with geocoded residential addresses for all case-patients with laboratory-confirmed influenza reported through passive surveillance. An automated daily analysis used the geocoded building identification number, approximate text matching, and key-word searches to identify influenza in residents of LTCFs for review and follow-up by surveillance coordinators. Our aim was to determine whether the building analysis improved prospective outbreak detection during the 2013-2014 influenza season. RESULTS: Of 119 outbreaks identified in LTCFs, 109 (92%) were ever detected by the building analysis, and 55 (46%) were first detected by the building analysis. Of the 5,953 LTCF staff and residents who received antiviral prophylaxis during the 2013-2014 season, 929 (16%) were at LTCFs where outbreaks were initially detected by the building analysis. CONCLUSIONS: A novel building-level analysis improved influenza outbreak identification in LTCFs in NYC, prompting timely infection control measures.

Refining historical limits method to improve disease cluster detection, New York City, New York, USA.

Since the early 2000s, the Bureau of Communicable Disease of the New York City Department of Health and Mental Hygiene has analyzed reportable infectious disease data weekly by using the historical limits method to detect unusual clusters that could represent outbreaks. This method typically produced too many signals for each to be investigated with available resources while possibly failing to signal during true disease outbreaks. We made method refinements that improved the consistency of case inclusion criteria and accounted for data lags and trends and aberrations in historical data. During a 12-week period in 2013, we prospectively assessed these refinements using actual surveillance data. The refined method yielded 74 signals, a 45% decrease from what the original method would have produced. Fewer and less biased signals included a true citywide increase in legionellosis and a localized campylobacteriosis cluster subsequently linked to live-poultry markets. Future evaluations using simulated data could complement this descriptive assessment.

Reducing sibling conflict in maltreated children placed in foster homes.

Sibling aggression among maltreated children placed in foster homes is linked to other externalizing problems and placement disruption. The reduction of sibling conflict and aggression may be achieved via a multicomponent ecologically focused intervention for families in the foster care system. The focus of the study is to evaluate the feasibility and short-term effectiveness of a transtheoretical intervention model targeting sibling pairs and their foster parent that integrates family systems, social learning theory, and a conflict mediation perspective. In this pilot study, sibling pairs (N = 22) and their foster parent were randomized into a three-component intervention (n = 13) or a comparison (n = 9) group. Promoting Sibling Bonds (PSB) is an 8-week prevention intervention targeting maltreated sibling pairs ages 5-11 years placed together in a foster home. The siblings, parent, and joint components were delivered in a program package at the foster agency by a trained two-clinician team. Average attendance across program components was 73 %. Outcomes in four areas were gathered at pre- and postintervention: observed sibling interaction quality (positive and negative) including conflict during play, and foster parent reports of mediation strategies and sibling aggression in the foster home. At postintervention, adjusting for baseline scores and child age, intervention pairs showed higher positive (p < 0.001) and negative (p < 0.05) interaction quality and lower sibling conflict during play (p < 0.01) than comparison pairs. Foster parents in the intervention group reported a higher number of conflict mediation strategies than those in the comparison group (p < 0.001). Foster parents in the intervention group reported lower sibling physical aggression from the older toward the younger child than those in the comparison group (p < 0.05). Data suggest that the PSB intervention is a promising approach to reduce conflict and promote parental mediation, which together may reduce sibling aggression in the foster home.

An assessment of the impact of the JSY cash transfer program on maternal mortality reduction in Madhya Pradesh, India.

BACKGROUND: The Indian Janani Suraksha Yojana (JSY) program is a demand-side program in which the state pays women a cash incentive to deliver in an institution, with the aim of reducing maternal mortality. The JSY has had 54 million beneficiaries since inception 7 years ago. Although a number of studies have demonstrated the effect of JSY on coverage, few have examined the direct impact of the program on maternal mortality. OBJECTIVE: To study the impact of JSY on maternal mortality in Madhya Pradesh (MP), one of India's largest provinces. DESIGN: By synthesizing data from various sources, district-level maternal mortality ratios (MMR) from 2005 to 2010 were estimated using a Bayesian spatio-temporal model. Based on these, a mixed effects multilevel regression model was applied to assess the impact of JSY. Specifically, the association between JSY intensity, as reflected by 1) proportion of JSY-supported institutional deliveries, 2) total annual JSY expenditure, and 3) MMR, was examined. RESULTS: The proportion of all institutional deliveries increased from 23.9% in 2005 to 55.9% in 2010 province-wide. The proportion of JSY-supported institutional deliveries rose from 14% (2005) to 80% (2010). MMR declines in the districts varied from 2 to 35% over this period. Despite the marked increase in JSY-supported delivery, our multilevel models did not detect a significant association between JSY-supported delivery proportions and changes in MMR in the districts. The results from the analysis examining the association between MMR and JSY expenditure are similar. CONCLUSIONS: Our analysis was unable to detect an association between maternal mortality reduction and the JSY in MP. The high proportion of institutional delivery under the program does not seem to have converted to lower mortality outcomes. The lack of significant impact could be related to supply-side constraints. Demand-side programs like JSY will have a limited effect if the supply side is unable to deliver care of adequate quality.

Mortality in Iraq associated with the 2003-2011 war and occupation: findings from a national cluster sample survey by the university collaborative Iraq Mortality Study.

BACKGROUND: Previous estimates of mortality in Iraq attributable to the 2003 invasion have been heterogeneous and controversial, and none were produced after 2006. The purpose of this research was to estimate direct and indirect deaths attributable to the war in Iraq between 2003 and 2011. METHODS AND FINDINGS: We conducted a survey of 2,000 randomly selected households throughout Iraq, using a two-stage cluster sampling method to ensure the sample of households was nationally representative. We asked every household head about births and deaths since 2001, and all household adults about mortality among their siblings. We used secondary data sources to correct for out-migration. From March 1, 2003, to June 30, 2011, the crude death rate in Iraq was 4.55 per 1,000 person-years (95% uncertainty interval 3.74-5.27), more than 0.5 times higher than the death rate during the 26-mo period preceding the war, resulting in approximately 405,000 (95% uncertainty interval 48,000-751,000) excess deaths attributable to the conflict. Among adults, the risk of death rose 0.7 times higher for women and 2.9 times higher for men between the pre-war period (January 1, 2001, to February 28, 2003) and the peak of the war (2005-2006). We estimate that more than 60% of excess deaths were directly attributable to violence, with the rest associated with the collapse of infrastructure and other indirect, but war-related, causes. We used secondary sources to estimate rates of death among emigrants. Those estimates suggest we missed at least 55,000 deaths that would have been reported by households had the households remained behind in Iraq, but which instead had migrated away. Only 24 households refused to participate in the study. An additional five households were not interviewed because of hostile or threatening behavior, for a 98.55% response rate. The reliance on outdated census data and the long recall period required of participants are limitations of our study. CONCLUSIONS: Beyond expected rates, most mortality increases in Iraq can be attributed to direct violence, but about a third are attributable to indirect causes (such as from failures of health, sanitation, transportation, communication, and other systems). Approximately a half million deaths in Iraq could be attributable to the war. Please see later in the article for the Editors' Summary.

Age-specific and sex-specific mortality in 187 countries, 1970-2010: a systematic analysis for the Global Burden of Disease Study 2010.

BACKGROUND: Estimation of the number and rate of deaths by age and sex is a key first stage for calculation of the burden of disease in order to constrain estimates of cause-specific mortality and to measure premature mortality in populations. We aimed to estimate life tables and annual numbers of deaths for 187 countries from 1970 to 2010. METHODS: We estimated trends in under-5 mortality rate (children aged 0-4 years) and probability of adult death (15-59 years) for each country with all available data. Death registration data were available for more than 100 countries and we corrected for undercount with improved death distribution methods. We applied refined methods to survey data on sibling survival that correct for survivor, zero-sibling, and recall bias. We separately estimated mortality from natural disasters and wars. We generated final estimates of under-5 mortality and adult mortality from the data with Gaussian process regression. We used these results as input parameters in a relational model life table system. We developed a model to extrapolate mortality to 110 years of age. All death rates and numbers have been estimated with 95% uncertainty intervals (95% UIs). FINDINGS: From 1970 to 2010, global male life expectancy at birth increased from 56·4 years (95% UI 55·5-57·2) to 67·5 years (66·9-68·1) and global female life expectancy at birth increased from 61·2 years (60·2-62·0) to 73·3 years (72·8-73·8). Life expectancy at birth rose by 3-4 years every decade from 1970, apart from during the 1990s (increase in male life expectancy of 1·4 years and in female life expectancy of 1·6 years). Substantial reductions in mortality occurred in eastern and southern sub-Saharan Africa since 2004, coinciding with increased coverage of antiretroviral therapy and preventive measures against malaria. Sex-specific changes in life expectancy from 1970 to 2010 ranged from gains of 23-29 years in the Maldives and Bhutan to declines of 1-7 years in Belarus, Lesotho, Ukraine, and Zimbabwe. Globally, 52·8 million (95% UI 51·6-54·1 million) deaths occurred in 2010, which is about 13·5% more than occurred in 1990 (46·5 million [45·7-47·4 million]), and 21·9% more than occurred in 1970 (43·3 million [42·2-44·6 million]). Proportionally more deaths in 2010 occurred at age 70 years and older (42·8% in 2010 vs 33·1% in 1990), and 22·9% occurred at 80 years or older. Deaths in children younger than 5 years declined by almost 60% since 1970 (16·4 million [16·1-16·7 million] in 1970 vs 6·8 million [6·6-7·1 million] in 2010), especially at ages 1-59 months (10·8 million [10·4-11·1 million] in 1970 vs 4·0 million [3·8-4·2 million] in 2010). In all regions, including those most affected by HIV/AIDS, we noted increases in mean ages at death. INTERPRETATION: Despite global and regional health crises, global life expectancy has increased continuously and substantially in the past 40 years. Yet substantial heterogeneity exists across age groups, among countries, and over different decades. 179 of 187 countries have had increases in life expectancy after the slowdown in progress in the 1990s. Efforts should be directed to reduce mortality in low-income and middle-income countries. Potential underestimation of achievement of the Millennium Development Goal 4 might result from limitations of demographic data on child mortality for the most recent time period. Improvement of civil registration system worldwide is crucial for better tracking of global mortality. FUNDING: Bill & Melinda Gates Foundation.

Assessment of population-level effect of Avahan, an HIV-prevention initiative in India.

BACKGROUND: The aim of Avahan, the India AIDS Initiative, was to reduce HIV transmission in the general population through large-scale prevention interventions focused on high-risk groups. It was launched in 2003 in six states with a total population of 300 million and a high HIV burden. We assessed the population-level effect of the first phase of Avahan (2003-08). METHODS: Population prevalence was estimated by use of adjustment factors from the national HIV sentinel surveillance data obtained annually from antenatal clinics. A mixed-effects multilevel regression model was developed to estimate the association between intervention intensity and population HIV prevalence trends, taking into account differences in the underlying epidemic trends in states and other potential confounders, and to estimate the number of HIV infections averted with Avahan. FINDINGS: 80 (61%) of 131 districts in the six Avahan states received funding from Avahan for HIV prevention, as the only or shared source. Greater intensity of Avahan, measured as amount of grant per HIV population (medians US$24-432 in the six states), was significantly associated with lower HIV prevalence in Andhra Pradesh (p=0·004), Karnataka (p=0·004), and Maharashtra (p=0·008) states; this association was not significant in Tamil Nadu (p=0·06), Manipur (p=0·62), and Nagaland (p=0·67). Overall, we estimated that 100,178 HIV infections (95% CI 25,897-207,713) were averted at the population level from 2003 up to 2008 as a result of Avahan. INTERPRETATION: The results of our analysis suggest that Avahan had a beneficial effect in reducing HIV prevalence at the population level over 5 years of programme implementation in some of the states. With stagnating funding for HIV prevention globally, our findings support investment in well planned and managed HIV prevention programmes in low-income and middle-income countries. FUNDING: Bill & Melinda Gates Foundation.