In 1997, new cases of TB totaled an estimated 7.96 million (range, 6.3 million-11.1 million), including 3.52 million (2.8 million-4.9 million) cases (44%) of infectious pulmonary disease (smear-positive), and there were 16.2 million (12.1 million-22.5 million) existing cases of disease. An estimated 1.87 million (1.4 million-2.8 million) people died of TB and the global case fatality rate was 23% but exceeded 50% in some African countries with high HIV rates. Global prevalence of MTB infection was 32% (1.86 billion people). Eighty percent of all incident TB cases were found in 22 countries, with more than half the cases occurring in 5 Southeast Asian countries. Nine of 10 countries with the highest incidence rates per capita were in Africa. Prevalence of MTB/HIV coinfection worldwide was 0.18% and 640000 incident TB cases (8%) had HIV infection. The global burden of tuberculosis remains enormous, mainly because of poor control in Southeast Asia, sub-Saharan Africa, and eastern Europe, and because of high rates of M tuberculosis and HIV coinfection in some African countries.

We investigate the health consequences of changes in the supply of fast food using the exact geographical location of fast food restaurants. Specifically, we ask how the supply of fast food affects the obesity rates of 3 million school children and the weight gain of over 3 million pregnant women. We find that among 9th grade children, a fast food restaurant within a tenth of a mile of a school is associated with at least a 5.2 percent increase in obesity rates. There is no discernable effect at .25 miles and at .5 miles. Among pregnant women, models with mother fixed effects indicate that a fast food restaurant within a half mile of her residence results in a 1.6 percent increase in the probability of gaining over 20 kilos, with a larger effect at .1 miles. The effect is significantly larger for African-American and less educated women. For both school children and mothers, the presence of non-fast food restaurants is uncorrelated with weight outcomes. Moreover, proximity to future fast food restaurants is uncorrelated with current obesity and weight gain, conditional on current proximity to fast food. The implied effects of fast-food on caloric intake are at least one order of magnitude larger for students than for mothers, consistent with smaller travel cost for adults.

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We investigate how changes in the supply of fast food restaurants affect weight outcomes of 3 million children and 3 million pregnant women. Among ninth graders, a fast food restaurant within 0.1 miles of a school results in a 5.2 percent increase in obesity rates. Among pregnant women, a fast-food restaurant within 0.5 miles of residence results in a 1.6 percent increase in the probability of gaining over 20 kilos. The implied effects on caloric intake are one order of magnitude larger for children than for mothers, consistent with smaller travel cost for adults. Non-fast food restaurants and future fast-food restaurants are uncorrelated with weight outcomes. (JEL I12, J13, J16, L83)

Restricted access to primary care can lead to avoidable, excessive use of expensive emergency care. Since 2013, partly to alleviate overcrowding at the Accident & Emergency (A&E) units of hospitals, the UK has been piloting 7-day opening of General Practitioner (GP) practices to improve primary care access for patients. We evaluate the impact of these pilots on patient attendances at A&E. We estimate that 7-day GP opening has reduced A&E attendances by patients of pilot practices by 9.9% with most of the impact on weekends which see A&E attendances fall by 17.9%. The effect is non-monotonic in case severity with most of the fall occurring in cases of moderate severity. An additional finding is that there is also a 9.9% fall in weekend hospital admissions (from A&E) which is entirely driven by a fall in admissions of elderly patients. The impact on A&E attendances appears to be bigger among wealthier patients. We present evidence in support of a causal interpretation of our results and discuss policy implications.

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This paper tests for bias in consumer lending decisions using administrative data from a high-cost lender in the United Kingdom. We motivate our analysis using a simple model of bias in lending, which predicts that profits should be identical for loan applicants from different groups at the margin if loan examiners are unbiased. We identify the profitability of marginal loan applicants by exploiting variation from the quasi-random assignment of loan examiners.We find significant bias against both immigrant and older loan applicants when using the firm's preferred measure of long-run profits. In contrast, there is no evidence of bias when using a short-run measure used to evaluate examiner performance, suggesting that the bias in our setting is due to the misalignment of firm and examiner incentives. We conclude by showing that a decision rule based on machine learning predictions of long-run profitability can simultaneously increase profits and eliminate bias.

We investigate whether food price subsidies affect household nutrition using a dramatic expansion of the availability of subsidized rice in the Indian state of Chhattisgarh in the early 2000's. Households in Chhattisgarh improved their nutritional intake relative to households in districts bordering the state as the availability of subsidized rice expanded. This increase is driven by households most likely to be eligible for rice subsidies, and we do not find evidence that households least likely to be eligible changed their diet. These results differ from recent studies suggesting that food subsidies may have little effect on nutrition.