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Food adulteration with toxic chemicals is a global public health threat. Lead chromate adulterated spices have been linked with lead poisoning in many countries, from Bangladesh to the United States. This study systematically assessed lead chromate adulteration in turmeric, a spice that is consumed daily across South Asia. Our study focused on four understudied countries that produce >80 % of the world's turmeric and collectively include 1.7 billion people, 22 % of the world's population. Turmeric samples were collected from wholesale and retail bazaars from 23 major cities across India, Pakistan, Sri Lanka, and Nepal between December 2020 and March 2021. Turmeric samples were analyzed for lead and chromium concentrations and maximum child blood lead levels were modeled in regions where samples had detectable lead. A total of 356 turmeric samples were collected, including 180 samples of dried turmeric roots and 176 samples of turmeric powder. In total, 14 % of the samples (n = 51) had detectable lead above 2 μg/g. Turmeric samples with lead levels greater than or equal to 18 μg/g had molar ratios of lead to chromium near 1:1, suggestive of lead chromate adulteration. Turmeric lead levels exceeded 1000 μg/g in Patna (Bihar, India) as well as Karachi and Peshawar (Pakistan), resulting in projected child blood lead levels up to 10 times higher than the CDC's threshold of concern. Given the overwhelmingly elevated lead levels in turmeric from these locations, urgent action is needed to halt the practice of lead chromate addition in the turmeric supply chain.

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Science of The Total Environment
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Stephen P. Luby
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2024, 175003
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A team of SHP faculty and researchers, together with Stanford Medicine graduate and medical students and in collaboration with colleagues at CIDE in Mexico, have launched a modeling framework to investigate the epidemiology of COVID-19 and to support pro-active resource planning and policy evaluations for diverse populations and geographies — including California, Mexico and India.

The Stanford-CIDE Coronavirus Simulation Model — or SC-COSMO — incorporates realistic demography and patterns of contacts sufficient for transmission of the virus that has infected more than 2 million people worldwide and claimed more than 125,600 lives, according to the widely used Johns Hopkins COVID-19 map which is updated several times a day.

The SC-COSMO model also incorporates non-pharmaceutical interventions, such as social distancing, timing and effects on reductions in contacts which may differ by demography.

Jeremy Goldhaber-Fiebert, an associate professor of medicine at Stanford Health Policy, is the principal investigator of the project, along with Fernando Alarid-Escudero, an assistant professor at the Center for Research and Teaching in Economics (CIDE) in Mexico and Jason Andrews, an assistant professor of medicine (infectious diseases) at Stanford Medicine. Other SHP faculty among the 20 investigators and staff members who are working on the project are Joshua Salomon and David Studdert, both professors of medicine.

The model also allows for the comparison of many future what-if scenarios and how they might impact outcomes over time and cumulatively.

The SC-COSMO team is a multi-disciplinary, multi-institutional team including expertise and experience in infectious disease, epidemiology, mathematical modeling and simulation, statistics, decision science, health policy, health law and health economics.

“As COVID-19 transmission occurs throughout the world’s diverse populations, it is critical to efficiently model and forecast its future spread between and within these populations and to appropriately reflect uncertainty in modeled outcomes,” Goldhaber-Fiebert said. “Doing so supports timely resource planning and decision making between potentially appropriate and effective interventions that balance the trade-offs they embody.”

The team is currently working on three projects:

  1. The researchers are providing California with county-level COVID-19 estimates for such things as the number of infections, detected cases and projections of future needs for hospital and ICU beds, personal protective equipment (PPE) and ventilators.
  2. The project is working on potential strategies to mitigate the COVID-19 pandemic in Mexico by focusing on three specific objectives: collecting, synthesizing and openly sharing the most relevant and useful data; accelerating the development of the SC-COSMO model and its adaptation to the Mexican situation; and identifying a set of mitigation strategies, comparing the health and economic consequences in the population in the medium and long term.
  3. They are developing forecast models of the COVID-19 epidemic in India with the Wadhwani Institute of Artificial Intelligence and its Indian government partners, providing a rapid response to urgent needs for planning and resource allocation.

 

jeremy

Jeremy Goldhaber-Fiebert

Associate Professor of Medicine
His research focuses on complex policy decisions surrounding the prevention and management of increasingly common, chronic diseases and the life course impact of exposure to their risk factors.

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Federalism Meets the COVID-19 Pandemic: Thinking Globally, Acting Locally

Federalism Meets the COVID-19 Pandemic: Thinking Globally, Acting Locally
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The Stanford-CIDE Coronavirus Simulation Model — or SC-COSMO — incorporates realistic demography and patterns to investigate resource planning and policy evaluations for diverse populations and geographies in California, Mexico and India.

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The decreasing effectiveness of antimicrobial agents is a global public health threat, yet risk factors for community-acquired antimicrobial resistance (CA-AMR) in low-income settings have not been clearly elucidated. Our aim was to identify risk factors for CA-AMR with extended-spectrum β-lactamase (ESBL)–producing organisms among urban-dwelling women in India. We collected microbiological and survey data in an observational study of primigravidae women in a public hospital in Hyderabad, India. We analyzed the data using multivariate logistic and linear regression and found that 7% of 1,836 women had bacteriuria; 48% of isolates were ESBL-producing organisms. Women in the bottom 50th percentile of income distribution were more likely to have bacteriuria (adjusted odds ratio 1.44, 95% CI 0.99–2.10) and significantly more likely to have bacteriuria with ESBL-producing organisms (adjusted odds ratio 2.04, 95% CI 1.17–3.54). Nonparametric analyses demonstrated a negative relationship between the prevalence of ESBL and income.

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Emerging Infectious Diseases Journal
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Douglas K. Owens
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Objective To evaluate the impact on the quality of the care provided for childhood diarrhoea and pneumonia in Bihar, India of a large-scale, social franchising and telemedicine programme– the World Health Partners’ Sky Program.

Methods We investigated changes associated with the Sky Program in the knowledge and performance of health-care providers by assessing a representative sample of 810 providers in areas where the Program was and was not implemented. Providers were assessed using hypothetical patient vignettes and the standardized patient method both before and after Program implementation in 2011 and 2014, respectively. Differences in providers’ performance between implementation and nonimplementation areas were assessed using multivariate difference-in-difference linear regression models.

Findings The Sky Program did not significantly improve health-care providers’ knowledge or performance with regard to childhood diarrhoea or pneumonia in Bihar. The large gap between knowledge of appropriate care and the care actually delivered persisted.

Conclusion Social franchising has received attention globally as a model for delivering high-quality care in rural areas in the developing world but supporting data are scarce. Our findings emphasize the need for sound empirical evidence before social franchising programmes are scaled up.

 

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Bulletin of the World Health Organization
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Jeremy Goldhaber-Fiebert
Grant Miller
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We study how agents respond to performance incentives according to key personality traits (conscientiousness and neuroticism) through a field experiment offering financial incentives for improving maternal and neonatal health outcomes to rural Indian doctors. More conscientious providers performed better – but improved less – under performance incentives.  The effect of the performance incentives was also smaller for providers with higher levels of neuroticism. Our results contribute to a growing body of empirical research on heterogeneous responses to incentives and have implications for worker selection.

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American Economic Review
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Grant Miller
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Beth Duff-Brown
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An Indian businessman approached Stanford Medicine in 2005 with an outlandish proposition: Help us build an ambulance system across the sprawling South Asia nation, which is home to 10 percent of the world’s traffic deaths.

S.V. Mahadevan, MD, an associate professor of emergency medicine at Stanford Medicine, was skeptical the nonprofit GVK EMRI (Emergency Management and Research Institute) could truly pull it off.

They only had 14 ambulances in the world’s second most populous nation.

Today the system has expanded to a fleet of nearly 10,000 ambulances, manned by some 20,000 medical professionals who ply the roads in cities and rural villages to provide access to emergency care to 750 million people — three-quarters of India’s population — according to a story in Stanford Medicine magazine last year.

“It’s hard to fathom what this system has done in 10 years,” said Mahadevan, founder of Stanford Emergency Medicine International, which has provided medical expertise to GVK EMRI over the last decade, helping to train the EMTs who now belong to the largest ambulance service in the developing world.

“It could be regarded as one of the most important advances in global medicine in the world today," he said.

Yet up until now there has been no analytical research on the impact of the ambulance service. Though EMRI says its 911-like service has saved more than 1.4 million lives in its first decade, there has been no published research to back up that claim.

Now, research by Stanford Health Policy scholars published in the October edition of the health policy journal, Health Affairs, indicates EMRI’s system has had a significant impact on saving the lives of newborns and infants, one of the most challenging health dilemmas plaguing India today.

Focusing on the first two states served by GVK EMRI — with a combined population of 145 million — their results show that the organization’s services have reduced infant and neonatal mortality rates by at least 2 percent in high-mortality areas of the western state of Gujarat. There were similar effects statewide in the southeastern state of Andhra Pradesh.

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"I've worked on various issues related to women and children's health in Asia for many years, and one of the most frustratingly stubborn problems is preventable infant and maternal deaths,” said Kimberly Singer Babiarz, a research scholar at Stanford Health Policy and lead author of the paper.

“With our modern medical knowledge, childbirth should not be so risky and newborns should not be dying at such high rates,” said Babiarz.

India has 28 maternal neonatal or infant deaths per 1,000 live births, according to the World Bank, making it one of the highest in the world. The global average is 19.2 deaths per 1,000 births; the rate drops to 4 in North America.

“These issues are particularly compelling to me as a mother,” Babiarz said. “It's wonderful to find a model that has found some success in connecting mothers and their infants with high-quality and timely emergency care when it is most needed.”

The authors used electronic service records from GVK EMRI, matched to population-representative surveys from the International Institute for Population Sciences, and their own survey that they conducted in Gujarat in 2010 through the Collaboration for Health System Improvement and Impact Evaluation in India. The combined surveys include information on over 16,000 live births.

The public-private nonprofit provides its services free of charge and most of its beneficiaries are the poorest of the poor. Each state contributes to the ambulance system, as does the federal government. It also depends on private philanthropy among some of India’s wealthiest industrialists.

The School of Medicine in 2007 signed a formal agreement to develop an educational curriculum and train the initial group of 180 skilled paramedics and instructors. Over the years, the Stanford instructors have learned to tailor the curriculum to local needs.

About one-third of the toll-free calls to 108 — an auspicious number in India — are from women in labor. Deliveries have traditionally been done at home, particularly in rural villages, where women often die of complications. So the Stanford team has since designed a special obstetrics curriculum and helped create the country’s first protocols for obstetric care.

 

 

Grant Miller, an associate professor of medicine, core faculty member at Stanford Health Policy and senior author of the study, has worked on many health policy projects in India over the years. The results aren’t always hopeful.

“I’ve conducted a number of evaluations of large-scale health programs in India, and there are disappointingly few programs and policies that we’ve found to be effective,” said Miller, who is also director of the Stanford Center for International Development and a senior fellow at the Stanford Institute for Economic Policy Research and the Freeman Spogli Institute for International Studies. “So it’s exciting to find one that may have worked quite well.”

Miller and his fellow authors note, however, that further research on emergency medical services in other Indian states and by other providers is still needed.

“We need to do a lot more work — but these results suggest that something important has happened,” he said. “With the release of more population-representative data from more states, we’re eager to expand our analysis to the rest of the country.”

Stanford Medicine’s Center for Innovation in Global Health also supported the authors’ research in India.

Ruthann Richter, director of media relations for the medical school's Office of Communication & Public Affairs, contributed to this story.

 

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GVK EMRI paramedics help a woman into one of the 10,000 ambulances the nonprofit has operating around India today.
Siddhartha Jain
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India celebrates the 10th anniversary of its Emergency Management and Research Institute (EMRI), the world's largest ambulance service that is saving the lives of the poorest Indian residents free of charge. Stanford Medicine experts, who trained responders in emergency medical procedures, joined EMRI to celebrate the program's success. Read More

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Background

Demographic and socioeconomic changes such as increasing urbanization, migration, and female education shape population health in many low- and middle-income countries. These changes are rarely reflected in computational epidemiological models, which are commonly used to understand population health trends and evaluate policy interventions. Our goal was to create a “backbone” simulation modeling approach to allow computational epidemiologists to explicitly reflect changing demographic and socioeconomic conditions in population health models.

Methods

We developed, evaluated, and “open-sourced” a generalized approach to incorporate longitudinal, commonly available demographic and socioeconomic data into epidemiological simulations, illustrating the feasibility and utility of our approach with data from India. We constructed a series of nested microsimulations of increasing complexity, calibrating each model to longitudinal sociodemographic and vital registration data. We then selected the model that was most consistent with the data (i.e., greater accuracy) while containing the fewest parameters (i.e., greater parsimony). We validated the selected model against additional data sources not used for calibration.

Results

We found that standard computational epidemiology models that do not incorporate demographic and socioeconomic trends quickly diverged from past mortality and population size estimates, while our approach remained consistent with observed data over decadal time courses. Our approach additionally enabled the examination of complex relations between demographic, socioeconomic and health parameters, such as the relationship between changes in educational attainment or urbanization and changes in fertility, mortality, and migration rates.

Conclusions

Incorporating demographic and socioeconomic trends in computational epidemiology is feasible through the “open source” approach, and could critically alter population health projections and model-based evaluations of health policy interventions in unintuitive ways.

 

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Population Health Metrics
Authors
Jeremy Goldhaber-Fiebert
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