Macartan Humphreys’s research while affiliated with Columbia University and other places

Objectives: Most low-income countries are characterized by poor health infrastructures and lack systems needed to timely detect and control disease outbreaks, such as the 2014-16 Ebola Viral Disease and COVID-19. In such contexts, a “One Health” approach, which involves investing in both human and animal health systems, plausibly improves local health outcomes by enabling early detection of zoonotic diseases before they are transmitted to humans, and by timely triggering a health system response needed to mitigate possible outbreaks. There is an urgent call to translate One Health into action and create inclusive and sustainable policies. There is, however, little direct evidence on the gains from One Health approaches. We contribute here by using a randomised intervention to assess the impact of a participatory community-based One Health program. Evidence before this study: A 2016 systematic review searched Scopus, PubMed, and ISI Web of Science using the term “One Health”, restricting publication date between 2003 and 2015.1 The search yielded 1,839 unique articles, but only four evaluated a One Health intervention using quantitative metrics. We performed the same search on 10 April 2023. Reflecting the burgeoning interest in One Health, we found an additional 9,715 unique articles. In total, only 17 articles, however, evaluated a One Health intervention implemented in real-world settings, utilizing quantitative metrics. Furthermore, these studies did not employ experimental methods to assess impact, relied on datasets with often only few observations, and focused exclusively on disease incidence. In the Supplementary Material (Appendix A), we provide a flowchart of the literature review and summarize these 17 related studies. Contribution: This study is the first cluster-randomised trial to assess the impact of a participatory community-based intervention establishing local health platforms employing a One Health approach. We evaluate the intervention at scale and explore the impact of the program on human health, but also on key intermediary outcomes like animal health and animal and human health behaviours. Design: Cluster-randomised control trial. Setting: 363 villages in rural Sierra Leone Participants: The Sierra Leone government and communities recruited, trained and installed Community Animal Health Workers (CAHWs) to work alongside Community Health Workers (CHWs) in 300 randomly selected rural villages in Sierra Leone. Another 63 villages were randomly selected as control sites and had CHWs exclusively. CAHWs provided essential animal health services, disseminated information regarding animal and human health best practices, and actively participated in surveillance efforts by reporting suspected disease symptoms to government supervisors. Main outcome measures: Survey based measures of human health, as well as key intermediary outcomes; including animal health, animal and human health-related behaviours, integration into public services, and household wealth. Results: In July and August 2017, the community-based One Health program successfully recruited, trained and installed CAHWs across 287 villages. Throughout the program's duration, spanning from July 2017 to July 2019, the CAHWs reported on 19,283 suspected disease-related events. Using survey data from over 2,500 respondents, collected in March and April 2020, we found no evidence for impacts on human health (-0.008 Standard Deviation Units (SDU), 95% CI -0.148, 0.133). The program did however significantly improve core intermediary outcomes, including animal health (0.164 SDU, 95% CI 0.017, 0.311), animal husbandry practices (0.255 SDU, 95% CI 0.087, 0.424), human health behaviours (0.187 SDU, 95% CI 0.025, 0.348), integration into public services (0.339 SDU, 95% CI 0.137, 0.541), and household wealth (0.163 SDU, 95% CI 0.053, 0.273). Conclusions: Participatory community-based One Health interventions can serve as a guide for policymakers that seek to strengthen the national health systems by improving disease surveillance and preventative practices that are expected to increase health security nationally and globally. More research is needed to understand how the magnitude, modality, and timing of the program and background conditions may shape program impact on human health. Trial registration: The trial was registered at the National Trail Registry (#21660), which is part of the ICTRP, and OSF (https://osf.io/9xfv3).

Suppose X and Y are binary exposure and outcome variables, and we have full knowledge of the distribution of Y, given application of X. We are interested in assessing whether an outcome in some case is due to the exposure. This “probability of causation” is of interest in comparative historical analysis where scholars use process tracing approaches to learn about causes of outcomes for single units by observing events along a causal path. The probability of causation is typically not identified, but bounds can be placed on it. Here, we provide a full characterization of the bounds that can be achieved in the ideal case that X and Y are connected by a causal chain of complete mediators, and we know the probabilistic structure of the full chain. Our results are largely negative. We show that, even in these very favorable conditions, the gains from positive evidence on mediators is modest.

Widespread acceptance of COVID-19 vaccines is crucial for achieving sufficient immunization coverage to end the global pandemic, yet few studies have investigated COVID-19 vaccination attitudes in lower-income countries, where large-scale vaccination is just beginning. We analyze COVID-19 vaccine acceptance across 15 survey samples covering 10 low- and middle-income countries (LMICs) in Asia, Africa and South America, Russia (an upper-middle-income country) and the United States, including a total of 44,260 individuals. We find considerably higher willingness to take a COVID-19 vaccine in our LMIC samples (mean 80.3%; median 78%; range 30.1 percentage points) compared with the United States (mean 64.6%) and Russia (mean 30.4%). Vaccine acceptance in LMICs is primarily explained by an interest in personal protection against COVID-19, while concern about side effects is the most common reason for hesitancy. Health workers are the most trusted sources of guidance about COVID-19 vaccines. Evidence from this sample of LMICs suggests that prioritizing vaccine distribution to the Global South should yield high returns in advancing global immunization coverage. Vaccination campaigns should focus on translating the high levels of stated acceptance into actual uptake. Messages highlighting vaccine efficacy and safety, delivered by healthcare workers, could be effective for addressing any remaining hesitancy in the analyzed LMICs. Survey data collected across ten low-income and middle-income countries (LMICs) in Asia, Africa and South America compared with surveys from Russia and the United States reveal heterogeneity in vaccine confidence in LMICs, with healthcare providers being trusted sources of information, as well as greater levels of vaccine acceptance in these countries than in Russia and the United States.

Background As vaccination campaigns are deployed worldwide, addressing vaccine hesitancy is of critical importance to ensure sufficient immunization coverage. We analyzed COVID-19 vaccine acceptance across 15 samples covering ten low- and middle- income countries (LMICs) in Asia, Africa, and South America, and two higher income countries (Russia and the United States). Methods Standardized survey responses were collected from 45,928 individuals between June 2020 and January 2021. We estimate vaccine acceptance with robust standard errors clustered at the study level. We analyze stated reasons for vaccine acceptance and hesitancy, and the most trusted sources for advice on vaccination, and we disaggregate acceptance rates by gender, age, and education level. Findings We document willingness to take a COVID-19 vaccine across LMIC samples, ranging from 67% (Burkina Faso) to 97% (Nepal). Willingness was considerably higher in LMICs (80%) than in the United States (65%) and Russia (30%). Vaccine acceptance was primarily explained by an interest in personal protection against the disease (91%). Concern about side effects (40%) was the most common reason for reluctance. Health workers were considered the most trusted sources of information about COVID-19 vaccines. Interpretation Given high levels of stated willingness to accept a COVID-19 vaccine across LMIC samples, our study suggests that prioritizing efficient and equitable vaccine distribution to LMICs will yield high returns in promoting immunization on a global scale. Messaging and other community-level interventions in these contexts should be designed to help translate intentions into uptake, and emphasize safety and efficacy. Trusted health workers are ideally positioned to deliver these messages.

Despite numerous journalistic accounts, systematic quantitative evidence on economic conditions during the ongoing COVID-19 pandemic remains scarce for most low- and middle-income countries, partly due to limitations of official economic statistics in environments with large informal sectors and subsistence agriculture. We assemble evidence from over 30,000 respondents in 16 original household surveys from nine countries in Africa (Burkina Faso, Ghana, Kenya, Rwanda, Sierra Leone), Asia (Bangladesh, Nepal, Philippines), and Latin America (Colombia). We document declines in employment and income in all settings beginning March 2020. The share of households experiencing an income drop ranges from 8 to 87% (median, 68%). Household coping strategies and government assistance were insufficient to sustain precrisis living standards, resulting in widespread food insecurity and dire economic conditions even 3 months into the crisis. We discuss promising policy responses and speculate about the risk of persistent adverse effects, especially among children and other vulnerable groups.

Do political and social features of states help explain the evolving distribution of reported Covid-19 deaths? We identify national-level political and social characteristics that past research suggests may help explain variation in a society's ability to respond to adverse shocks. We highlight four sets of arguments---focusing on (1) state capacity, (2) political institutions, (3) political priorities, and (4) social structures---and report on their evolving association with cumulative Covid-19 deaths. After accounting for a simple set of Lasso-chosen controls, we find that measures of government effectiveness, interpersonal and institutional trust, bureaucratic corruption and ethnic fragmentation are currently associated in theory-consistent directions. We do not, however, find associations between deaths and many other political and social variables that have received attention in public discussions, such as populist governments or women-led governments. Currently, the results suggest that state capacity is more important for explaining Covid-19 mortality than government accountability to citizens, with potential implications for how the disease progresses in high-income versus low-income countries. These patterns may change over time with the evolution of the pandemic, however. A dashboard with daily updates, extensions, and code is provided at https://wzb-ipi.github.io/corona/.

Banerjee, Duflo, and Kremer have had an enormous impact on scholarship on the political economy of development. But as RCTs have become more central in this field, political scientists have struggled to draw implications from proliferating micro-level studies for longstanding macro-level problems. We describe these challenges and point to recent innovations to help address them.

We examine whether gender quotas introduced by development agencies empower women. As part of a development program, an international organization created community management committees in 661 villages to oversee village level program expenditures. In a randomly selected half of these villages the organization required the committees to have gender parity. Using data on project choice from all participating villages, data on decision making in a later development project (105 villages), and data on citizen attitudes (200 villages), we find no evidence that gender parity requirements empower women. We discuss potential reasons for the null result, including weakness of these social interventions in terms of the engagement they generate, their time horizon, and the weak delegation of responsibilities.

Do citizens view state and traditional authorities as substitutes or complements? Past work has been divided on this question. Some scholars point to competition between attitudes toward these entities, suggesting substitution, whereas others highlight positive correlations, suggesting complementarity. Addressing this question, however, is difficult, as it requires assessing the effects of exogenous changes in the latent valuation of one authority on an individual’s support for another. We show that this quantity—a type of elasticity—cannot be inferred from correlations between support for the two forms of authority. We employ a structural model to estimate this elasticity of substitution using data from 816 villages in the Democratic Republic of Congo and plausibly exogenous rainfall and conflict shocks. Despite prima facie evidence for substitution logics, our model’s outcomes are consistent with complementarity; positive changes in citizen valuation of the chief appear to translate into positive changes in support for the government.