GAVI, the Vaccine Alliance.

This year's Lasker-Bloomberg Public Service Award goes to GAVI, the Vaccine Alliance, for providing sustained access to childhood vaccines around the globe, saving millions of lives, and highlighting the power of immunization to prevent disease.

Ending extreme poverty has a negligible impact on global greenhouse gas emissions.

Growing consumption is both necessary to end extreme poverty1and one of the main drivers of greenhouse gas emissions2, creating a potential tension between alleviating poverty and limiting global warming. Most poverty reduction has historically occurred because of economic growth3-6, which means that reducing poverty entails increasing not only the consumption of people living in poverty but also the consumption of people with a higher income. Here we estimate the emissions associated with the economic growth needed to alleviate extreme poverty using the international poverty line of US $2.15 per day (ref. 7). Even with historical energy- and carbon-intensity patterns, the global emissions increase associated with alleviating extreme poverty is modest, at 2.37 gigatonnes of carbon dioxide equivalent per year or 4.9% of 2019 global emissions. Lower inequality, higher energy efficiency and decarbonization of energy can ease this tension further: assuming the best historical performance, the emissions for poverty alleviation in 2050 will be reduced by 90%. More ambitious poverty lines require more economic growth in more countries, which leads to notably higher emissions. The challenge to align the development and climate objectives of the world is not in reconciling extreme poverty alleviation with climate objectives but in providing sustainable middle-income standards of living.

The effects of cash transfers on adult and child mortality in low- and middle-income countries.

Poverty is an important social determinant of health that is associated with increased risk of death1-5. Cash transfer programmes provide non-contributory monetary transfers to individuals or households, with or without behavioural conditions such as children's school attendance6,7. Over recent decades, cash transfer programmes have emerged as central components of poverty reduction strategies of many governments in low- and middle-income countries6,7. The effects of these programmes on adult and child mortality rates remains an important gap in the literature, however, with existing evidence limited to a few specific conditional cash transfer programmes, primarily in Latin America8-14. Here we evaluated the effects of large-scale, government-led cash transfer programmes on all-cause adult and child mortality using individual-level longitudinal mortality datasets from many low- and middle-income countries. We found that cash transfer programmes were associated with significant reductions in mortality among children under five years of age and women. Secondary heterogeneity analyses suggested similar effects for conditional and unconditional programmes, and larger effects for programmes that covered a larger share of the population and provided larger transfer amounts, and in countries with lower health expenditures, lower baseline life expectancy, and higher perceived regulatory quality. Our findings support the use of anti-poverty programmes such as cash transfers, which many countries have introduced or expanded during the COVID-19 pandemic, to improve population health.

A planetary health innovation for disease, food and water challenges in Africa.

Many communities in low- and middle-income countries globally lack sustainable, cost-effective and mutually beneficial solutions for infectious disease, food, water and poverty challenges, despite their inherent interdependence1-7. Here we provide support for the hypothesis that agricultural development and fertilizer use in West Africa increase the burden of the parasitic disease schistosomiasis by fuelling the growth of submerged aquatic vegetation that chokes out water access points and serves as habitat for freshwater snails that transmit Schistosoma parasites to more than 200 million people globally8-10. In a cluster randomized controlled trial (ClinicalTrials.gov: NCT03187366) in which we removed invasive submerged vegetation from water points at 8 of 16 villages (that is, clusters), control sites had 1.46 times higher intestinal Schistosoma infection rates in schoolchildren and lower open water access than removal sites. Vegetation removal did not have any detectable long-term adverse effects on local water quality or freshwater biodiversity. In feeding trials, the removed vegetation was as effective as traditional livestock feed but 41 to 179 times cheaper and converting the vegetation to compost provided private crop production and total (public health plus crop production benefits) benefit-to-cost ratios as high as 4.0 and 8.8, respectively. Thus, the approach yielded an economic incentive-with important public health co-benefits-to maintain cleared waterways and return nutrients captured in aquatic plants back to agriculture with promise of breaking poverty-disease traps. To facilitate targeting and scaling of the intervention, we lay the foundation for using remote sensing technology to detect snail habitats. By offering a rare, profitable, win-win approach to addressing food and water access, poverty alleviation, infectious disease control and environmental sustainability, we hope to inspire the interdisciplinary search for planetary health solutions11 to the many and formidable, co-dependent global grand challenges of the twenty-first century.

Tackling psychosocial and capital constraints to alleviate poverty.

Many policies attempt to help extremely poor households build sustainable sources of income. Although economic interventions have predominated historically1,2, psychosocial support has attracted substantial interest3-5, particularly for its potential cost-effectiveness. Recent evidence has shown that multi-faceted 'graduation' programmes can succeed in generating sustained changes6,7. Here we show that a multi-faceted intervention can open pathways out of extreme poverty by relaxing capital and psychosocial constraints. We conducted a four-arm randomized evaluation among extremely poor female beneficiaries already enrolled in a national cash transfer government programme in Niger. The three treatment arms included group savings promotion, coaching and entrepreneurship training, and then added either a lump-sum cash grant, psychosocial interventions, or both the cash grant and psychosocial interventions. All three arms generated positive effects on economic outcomes and psychosocial well-being, but there were notable differences in the pathways and the timing of effects. Overall, the arms with psychosocial interventions were the most cost-effective, highlighting the value of including well-designed psychosocial components in government-led multi-faceted interventions for the extreme poor.

Machine learning and phone data can improve targeting of humanitarian aid.

The COVID-19 pandemic has devastated many low- and middle-income countries, causing widespread food insecurity and a sharp decline in living standards1. In response to this crisis, governments and humanitarian organizations worldwide have distributed social assistance to more than 1.5 billion people2. Targeting is a central challenge in administering these programmes: it remains a difficult task to rapidly identify those with the greatest need given available data3,4. Here we show that data from mobile phone networks can improve the targeting of humanitarian assistance. Our approach uses traditional survey data to train machine-learning algorithms to recognize patterns of poverty in mobile phone data; the trained algorithms can then prioritize aid to the poorest mobile subscribers. We evaluate this approach by studying a flagship emergency cash transfer program in Togo, which used these algorithms to disburse millions of US dollars worth of COVID-19 relief aid. Our analysis compares outcomes-including exclusion errors, total social welfare and measures of fairness-under different targeting regimes. Relative to the geographic targeting options considered by the Government of Togo, the machine-learning approach reduces errors of exclusion by 4-21%. Relative to methods requiring a comprehensive social registry (a hypothetical exercise; no such registry exists in Togo), the machine-learning approach increases exclusion errors by 9-35%. These results highlight the potential for new data sources to complement traditional methods for targeting humanitarian assistance, particularly in crisis settings in which traditional data are missing or out of date.

Social capital I: measurement and associations with economic mobility.

Social capital-the strength of an individual's social network and community-has been identified as a potential determinant of outcomes ranging from education to health1-8. However, efforts to understand what types of social capital matter for these outcomes have been hindered by a lack of social network data. Here, in the first of a pair of papers9, we use data on 21 billion friendships from Facebook to study social capital. We measure and analyse three types of social capital by ZIP (postal) code in the United States: (1) connectedness between different types of people, such as those with low versus high socioeconomic status (SES); (2) social cohesion, such as the extent of cliques in friendship networks; and (3) civic engagement, such as rates of volunteering. These measures vary substantially across areas, but are not highly correlated with each other. We demonstrate the importance of distinguishing these forms of social capital by analysing their associations with economic mobility across areas. The share of high-SES friends among individuals with low SES-which we term economic connectedness-is among the strongest predictors of upward income mobility identified to date10,11. Other social capital measures are not strongly associated with economic mobility. If children with low-SES parents were to grow up in counties with economic connectedness comparable to that of the average child with high-SES parents, their incomes in adulthood would increase by 20% on average. Differences in economic connectedness can explain well-known relationships between upward income mobility and racial segregation, poverty rates, and inequality12-14. To support further research and policy interventions, we publicly release privacy-protected statistics on social capital by ZIP code at https://www.socialcapital.org .

Estimating a social cost of carbon for global energy consumption.

Estimates of global economic damage caused by carbon dioxide (CO2) emissions can inform climate policy1-3. The social cost of carbon (SCC) quantifies these damages by characterizing how additional CO2 emissions today impact future economic outcomes through altering the climate4-6. Previous estimates have suggested that large, warming-driven increases in energy expenditures could dominate the SCC7,8, but they rely on models9-11 that are spatially coarse and not tightly linked to data2,3,6,7,12,13. Here we show that the release of one ton of CO2 today is projected to reduce total future energy expenditures, with most estimates valued between -US$3 and -US$1, depending on discount rates. Our results are based on an architecture that integrates global data, econometrics and climate science to estimate local damages worldwide. Notably, we project that emerging economies in the tropics will dramatically increase electricity consumption owing to warming, which requires critical infrastructure planning. However, heating reductions in colder countries offset this increase globally. We estimate that 2099 annual global electricity consumption increases by about 4.5 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in global mean surface temperature (GMST), whereas direct consumption of other fuels declines by about 11.3 exajoules (7 per cent of current global consumption) per one-degree-Celsius increase in GMST. Our finding of net savings contradicts previous research7,8, because global data indicate that many populations will remain too poor for most of the twenty-first century to substantially increase energy consumption in response to warming. Importantly, damage estimates would differ if poorer populations were given greater weight14.

High life satisfaction reported among small-scale societies with low incomes.

Global polls have shown that people in high-income countries generally report being more satisfied with their lives than people in low-income countries. The persistence of this correlation, and its similarity to correlations between income and life satisfaction within countries, could lead to the impression that high levels of life satisfaction can only be achieved in wealthy societies. However, global polls have typically overlooked small-scale, nonindustrialized societies, which can provide an alternative test of the consistency of this relationship. Here, we present results from a survey of 2,966 members of Indigenous Peoples and local communities among 19 globally distributed sites. We find that high average levels of life satisfaction, comparable to those of wealthy countries, are reported for numerous populations that have very low monetary incomes. Our results are consistent with the notion that human societies can support very satisfying lives for their members without necessarily requiring high degrees of monetary wealth.

How poverty is measured impacts who gets classified as impoverished.

We test whether the classification of households into poverty categories is meaningfully influenced by the poverty measurement approach that is employed. These classification techniques are widely used by governments, non-profit organizations, and development agencies for policy design and implementation. Using primary data collected in Ethiopia, Ghana, and Uganda, we find almost no agreement in how four commonly used approaches rank 16,150 households in terms of poverty status. This result holds for each country, for urban and rural households, and across the entire socio-economic distribution. Households' poverty rankings differ by an entire quartile on average. Conclusions about progress toward poverty alleviation goals may depend in large part on how poverty is measured.

Higher total energy costs strain the elderly, especially low-income, across 31 developed countries.

Addressing the total energy cost burden of elderly people is essential for designing equitable and effective energy policies, especially in responding to energy crisis in an aging society. It is due to the double impact of energy price hikes on households-through direct impact on fuel bills and indirect impact on the prices of goods and services consumed. However, while examining the household energy cost burden of the elderly, their indirect energy consumption and associated cost burden remain poorly understood. This study quantifies and compares the direct and indirect energy footprints and associated total energy cost burdens for different age groups across 31 developed countries. It reveals that the elderly have larger per capita energy footprints, resulting from higher levels of both direct and indirect energy consumption compared with the younger age groups. More importantly, the elderly, especially the low-income elderly, have a higher total energy cost burden rate. As the share of elderly in the total population rapidly grows in these countries, the larger per capita energy footprint and associated cost burden rate of elderly people would make these aging countries more vulnerable in times of energy crises. It is therefore crucial to develop policies that aim to reduce energy consumption and costs, improve energy efficiency, and support low-income elderly populations. Such policies are necessary to reduce the vulnerability of these aging countries to the energy crisis.

Absolute income mobility obscures marginalized children's disadvantages.

Intergenerational mobility captures the distance between the socioeconomic positions of parents versus their adult children. Researchers measure this distance in absolute and relative units, such as absolute dollars and relative ranks. Absolute and relative mobility often diverge. For example, absolute mobility can rise while relative mobility declines. How should scholars and policymakers understand this divergence? We conclude that they should understand it as follows: absolute mobility is less reflective than relative mobility of marginalized children's socioeconomic disadvantages. We base this conclusion on analyses of survey, administrative, and simulated data on income mobility in the contemporary United States. We analyze multiple points of difference in mobility, which facilitates the recognition of several asymmetries. First, high-income children's experiences weigh more heavily in absolute-mobility trends than low-income children's experiences, particularly when economic growth is positive. Second, this asymmetry is more characteristic of absolute- than relative-mobility trends. Third, absolute-mobility differences across demographic groups are more prone than relative-mobility differences to obscure marginalized groups' socioeconomic disadvantages. These asymmetries have policy implications: We caution that focusing on absolute mobility as a policy target can divert attention away from society's most disadvantaged children.

Residential mobility and persistently depressed voting among disadvantaged adults in a large housing experiment.

This study examines the impact of residential mobility on electoral participation among the poor by matching data from Moving to Opportunity, a US-based multicity housing-mobility experiment, with nationwide individual voter data. Nearly all participants in the experiment were Black and Hispanic families who originally lived in high-poverty public housing developments. Notably, the study finds that receiving a housing voucher to move to a low-poverty neighborhood decreased adult participants' voter participation for nearly two decades-a negative impact equal to or outpacing that of the most effective get-out-the-vote campaigns in absolute magnitude. This finding has important implications for understanding residential mobility as a long-run depressant of voter turnout among extremely low-income adults.

Air Pollution and Mortality at the Intersection of Race and Social Class.

BACKGROUND: Black Americans are exposed to higher annual levels of air pollution containing fine particulate matter (particles with an aerodynamic diameter of ≤2.5 µm [PM2.5]) than White Americans and may be more susceptible to its health effects. Low-income Americans may also be more susceptible to PM2.5 pollution than high-income Americans. Because information is lacking on exposure-response curves for PM2.5 exposure and mortality among marginalized subpopulations categorized according to both race and socioeconomic position, the Environmental Protection Agency lacks important evidence to inform its regulatory rulemaking for PM2.5 standards. METHODS: We analyzed 623 million person-years of Medicare data from 73 million persons 65 years of age or older from 2000 through 2016 to estimate associations between annual PM2.5 exposure and mortality in subpopulations defined simultaneously by racial identity (Black vs. White) and income level (Medicaid eligible vs. ineligible). RESULTS: Lower PM2.5 exposure was associated with lower mortality in the full population, but marginalized subpopulations appeared to benefit more as PM2.5 levels decreased. For example, the hazard ratio associated with decreasing PM2.5 from 12 µg per cubic meter to 8 µg per cubic meter for the White higher-income subpopulation was 0.963 (95% confidence interval [CI], 0.955 to 0.970), whereas equivalent hazard ratios for marginalized subpopulations were lower: 0.931 (95% CI, 0.909 to 0.953) for the Black higher-income subpopulation, 0.940 (95% CI, 0.931 to 0.948) for the White low-income subpopulation, and 0.939 (95% CI, 0.921 to 0.957) for the Black low-income subpopulation. CONCLUSIONS: Higher-income Black persons, low-income White persons, and low-income Black persons may benefit more from lower PM2.5 levels than higher-income White persons. These findings underscore the importance of considering racial identity and income together when assessing health inequities. (Funded by the National Institutes of Health and the Alfred P. Sloan Foundation.).

A multifaceted poverty reduction program has economic and behavioral consequences.

This paper examines the causal impact of poverty reduction interventions on the social preferences of the poor. A multifaceted poverty reduction program in China provides a setting for the use of a fuzzy regression discontinuity design. The design compares households with base-year income just below a preset criterion, who were more likely to receive the program treatment, with households just above the criterion. Five years after the program's launch, we conducted a lab-in-the-field experiment to measure the distributional preferences of household heads. Combining quasi-random variation from program rules with administrative census and experimental data, we find both economic and behavioral consequences of the program: It increased household income by 50% 5 y later, increased consistency with utility maximization by household heads, and increased their efficiency preference while reducing selfishness and leaving equality preference unchanged. Our findings advance scientific understanding of social preferences formation and highlight a broad perspective in evaluating poverty reduction interventions.

Distribution of capitalized benefits from land conservation.

Land conservation efforts throughout the United States sustain ecological benefits while generating wealth in the housing market through capitalization of amenities. This paper estimates the benefits of conservation that are capitalized into proximate home values and quantifies how those benefits are distributed across demographic groups. Using detailed property and household-level data from Massachusetts, we estimate that new land conservation led to $62 million in new housing wealth equity. However, houses owned by low-income or Black or Hispanic households are less likely to be located near protected areas, and hence, these populations are less likely to benefit financially. Direct study of the distribution of this new wealth from capitalized conservation is highly unequal, with the richest quartile of households receiving 43%, White households receiving 91%, and the richest White households receiving 40%, which is nearly 140% more than would be expected under equal distribution. We extend our analysis using census data for the entire United States and observe parallel patterns. We estimate that recent land conservation generated $9.8 billion in wealth through the housing market and that wealthier and White households benefited disproportionately. These findings suggest regressive and racially disparate incidence of the wealth benefits of land conservation policy.

Variability in excess deaths across countries with different vulnerability during 2020-2023.

Excess deaths provide total impact estimates of major crises, such as the COVID-19 pandemic. We evaluated excess death trajectories across countries with accurate death registration and population age structure data and assessed relationships with vulnerability indicators. Using the Human Mortality Database on 34 countries, excess deaths were calculated for 2020-2023 (to week 29, 2023) using 2017-2019 as reference, with adjustment for 5 age strata. Countries were divided into less and more vulnerable; the latter had per capita nominal GDP < $30,000, Gini > 0.35 for income inequality and/or at least ≥2.5% of their population living in poverty. Excess deaths (as proportion of expected deaths, p%) were inversely correlated with per capita GDP (r = -0.60), correlated with proportion living in poverty (r = 0.66), and modestly correlated with income inequality (r = 0.45). Incidence rate ratio for deaths was 1.062 (95% CI, 1.038-1.087) in more versus less vulnerable countries. Excess deaths started deviating in the two groups after the first wave. Between-country heterogeneity diminished gradually within each group. Less vulnerable countries had mean p% = -0.8% and 0.4% in 0-64 and >65-y-old strata. More vulnerable countries had mean p% = 7.0% and 7.2%, respectively. Lower death rates were seen in children of age 0-14 y during 2020-2023 versus prepandemic years. While the pandemic hit some countries earlier than others, country vulnerability dominated eventually the cumulative impact. Half the analyzed countries witnessed no substantial excess deaths versus prepandemic levels, while the others suffered major death tolls.

The epidemiology of Parkinson's disease.

The epidemiology of Parkinson's disease shows marked variations in time, geography, ethnicity, age, and sex. Internationally, prevalence has increased over and above demographic changes. There are several potential reasons for this increase, including the decline in other competing causes of death. Whether incidence is increasing, especially in women or in many low-income and middle-income countries where there is a shortage of high-quality data, is less certain. Parkinson's disease is more common in older people and men, and a variety of environmental factors have been suggested to explain why, including exposure to neurotoxic agents. Within countries, there appear to be ethnic differences in disease risk, although these differences might reflect differential access to health care. The cause of Parkinson's disease is multifactorial, and involves genetic and environmental factors. Both risk factors (eg, pesticides) and protective factors (eg, physical activity and tendency to smoke) have been postulated to have a role in Parkinson's disease, although elucidating causality is complicated by the long prodromal period. Following the establishment of public health strategies to prevent cardiovascular diseases and some cancers, chronic neurodegenerative diseases such as Parkinson's disease and dementia are gaining a deserved higher priority. Multipronged prevention strategies are required that tackle population-based primary prevention, high-risk targeted secondary prevention, and Parkinson's disease-modifying therapies for tertiary prevention. Future international collaborations will be required to triangulate evidence from basic, applied, and epidemiological research, thereby enhancing the understanding and prevention of Parkinson's disease at a global level.