Econ of Health & South Asia Midterm 1 Prep

The Demand for Health — Wagstaff (1986)

Objective: Explain Grossman's demand-for-health model to non-economists and apply it to prevention, health inequality and unemployment.

Findings: People produce health from inputs (food, housing, heating, medical care). Diminishing returns to inputs. Higher income → more inputs → better health, and an income loss hurts most at low incomes. Cheaper inputs or more education → better health.

Implications: Income supplements work best for the poor. Theory gives direction, not size, so pair with cost-effectiveness analysis.

The Demand for Health Care — Mwabu (2008)

Objective: Link demand for health care to health production and show how demand analysis guides policy. Findings: Care is a derived demand (wanted only because it produces health). Demand estimates show what drives care use (cost, distance, quality). Demand evidence alone isn't enough, you also need the care → health link. Implications: Target the barriers that keep the poor from seeking care. More spending helps only if the care actually produces health.

Health insurance enrollment and dropout in Nepal — Ranabhat (2020)

Objective: Measure enrollment and dropout in Nepal's social health insurance and identify what drives them. Findings: Enrollment and dropout vary widely by district and dropout is high. Main drivers are supply-side: drug shortages, unfriendly staff toward insured patients, staff steering patients to private clinics. Implications: Poor service quality, not just price, drives people out. Fix the facilities and benefit package to keep the program sustainable.

Moving towards universal health coverage — Lagomarsino (2012)

Objective: Compare national health insurance reforms toward UHC in nine developing countries in Africa and Asia. Findings: Common patterns: tax revenue subsidises target groups, risk pools broaden, money follows the patient. More people covered, bigger benefit packages, falling out-of-pocket spending. No two reforms are identical. Implications: Tax-funded subsidies are how the poor and informal workers get covered.

Determinants of life insurance consumption in South Asia — Sanjeewa (2019)

Objective: Identify what drives life insurance purchases in South Asia's emerging insurance markets. Findings: Uptake is linked to urbanisation and household finances (secondhand summary, verify). Implications: Rural and poor households are the least protected against income shocks from death or illness.

Determinants of enrolment in voluntary health insurance (Kerala) — Vellakkal (2013)

Objective: Find what drives enrolment in voluntary health insurance in Kerala, testing for income inequality and adverse selection. Findings: Income, education, health risk, awareness and insurance agents all matter. Richer households enrol more. No adverse selection (sicker people aren't the main buyers). Implications: Voluntary insurance leaves the poor behind. Raise awareness, improve agent incentives, pay claims reliably.

Progress towards UHC in South Asia, 2000–2030 — Rahman (2025)

Objective: Track and project UHC progress in seven South Asian countries on primary care coverage and financial protection. Findings: Coverage is rising (Sri Lanka, Bhutan lead, Afghanistan likely to miss). Financial protection is getting worse: catastrophic spending projected to more than double. Rural households trail. Government PHC spending and public insurance (India, Nepal) help. Implications: Coverage without financial protection pushes households into catastrophic spending. Fund primary care publicly.

Progress Toward UHC (5 South Asian countries) — Rahman (2017)

Objective: Measure UHC progress and inequality in Afghanistan, Bangladesh, India, Nepal and Pakistan. Findings: Access to basic care varies widely across and within countries. Financial protection is low in all five. Out-of-pocket payments are the main way care is funded, and coverage is unequal by wealth. Implications: The poorest are least covered and least protected. Reaching them is the core UHC challenge.

Health, Inequality, and Economic Development — Deaton (2003)

Objective: Test whether income inequality itself harms health (mainly mortality). Findings: No direct link from inequality to ill health. Raw correlations reflect other factors. A person's own absolute income matters, not income relative to others. Implications: Raise the incomes of the poor and provide public goods rather than narrowing the gap for its own sake.

Food insecurity, environment, institutional quality, and health outcomes — Azimi (2024)

Objective: Test how food insecurity, environmental degradation and inflation shocks affect life expectancy and mortality in South Asia, and whether institutions change the effect. Findings: Food insecurity, pollution and inflation shocks lower life expectancy and raise mortality (triple health constraints). Better institutions improve health and cushion these harms. Implications: Governance, food security and environmental policy are health policy.

Life expectancy and health care spending in South Asia — Dhungana (2024)

Objective: Estimate how health spending relates to life expectancy across South Asia. Findings: Health spending, schooling and income per head share a long-run relationship with life expectancy, and all three raise it. Implications: Sustained health spending pays off. Education and income growth are health policies too.

Decomposing socioeconomic inequality in maternal health care — Goli (2018)

Objective: Measure how much each socioeconomic factor contributes to unequal use of maternal care (Bangladesh, Nepal, Ethiopia, Zimbabwe). Findings: Maternal care use favours the better-off in all four countries. The main drivers of that inequality differ by country. Implications: One-size-fits-all policy won't close the gap. Each country must target its own drivers.

Health sector reform in South Asia — Islam (2002)

Objective: Examine the challenges and constraints facing health sector reform in South Asia. Findings (verify, no abstract): Health systems are fragmented, under-resourced, inefficient and gender-insensitive. Implications: Integrate single-disease programs into primary care, regionalise services, share costs between public and private sectors.

Poverty, inequality and health — Jayasinghe (2005)

Objective: Discuss how poverty and inequality shape health in South Asia. Findings: Short brief report, no abstract found (verify against course copy). Poverty and inequality drive poor health outcomes. Implications: Health policy must address poverty and inequality, not just medical care.

Progress in maternal and child health — Akseer (2017)

Objective: Assess progress in maternal, newborn and child health across South Asia and readiness for the SDGs. Findings: Under-5 mortality fell faster than the global average, but the region still has a large share of child deaths. Maternal mortality stays high in Afghanistan, Pakistan, Nepal. Pneumonia and diarrhoea are top preventable killers. Coverage gaps widest for the poorest and rural. Malnutrition persists. Implications: Target the poorest and rural. Poverty, malnutrition and low female empowerment remain the barriers.

Health inequalities in South Asia at the launch of SDGs — Thresia (2018)

Objective: Expose the health inequalities hidden behind Kerala's (and South Asia's) social progress and argue for political solutions. Findings: Stark inequalities remain: shorter lives, higher maternal and child mortality, gender discrimination. Driven by caste, class, gender, ethnicity and patriarchy. In Kerala, Dalits, minorities and women are left out. Implications: Health gaps are political, so they need political interventions, not just more services.

Non-communicable diseases in South Asia — Siegel (2014)

Objective: Describe the burden and trends of four NCDs in South Asia (cardiovascular disease, diabetes, cancer, COPD). Findings: NCD burden is rising faster than globally, pushed by ageing, development and urbanisation. Infectious, maternal and nutrition problems persist (double burden). Burden is largest among the affluent now, but risk factors concentrate among the poor. Implications: The burden will shift to the poor, who can least afford chronic care.

NCD Countdown 2030 — Bennett (2020)

Objective: Find the disease-specific improvements each country needs to meet SDG 3.4 (cut premature NCD deaths by a third, 2015–2030). Findings: Premature NCD deaths are falling in most countries, but too slowly. Every country has a feasible pathway. No country can get there by tackling one disease. Needs prevention, early detection and treatment together. Implications: Build a broad NCD response into health systems, especially primary care, not single-disease programs.

Burden of non-communicable diseases in South Asia — Pradhan (2025)

Objective: Measure the NCD burden in South Asia and decompose what drives changes in NCD deaths and DALYs. Findings: Prevalence stays above the global rate. Cardiovascular and respiratory incidence fell, diabetes and cancer rose. Population growth and ageing are the main drivers. Environmental risks are a bigger share than globally. Implications: Ageing will keep raising NCD costs. Needs risk-factor control, environmental policy and healthy-ageing strategies.

Impact of COVID-19 on essential RMNCH services — Gadsden (2024)

Objective: Measure how COVID-19 disrupted reproductive, maternal, newborn and child health services in the Southeast Asia region. Findings: Large disruptions across many services. Disruption was larger than countries' own WHO reports suggested. Five countries had no studies at all. Implications: Mothers and children lose care when health systems are stretched. Protect essential services in future crises.

Prevalence of anxiety and depression in South Asia during COVID-19 — Hossain (2021)

Objective: Estimate the pooled prevalence of anxiety and depression in South Asia during the pandemic (meta-analysis). Findings: Anxiety and depression were highly prevalent. India had the most studies, but Bangladesh and Pakistan had higher prevalence. Few studies and high variation. Implications: Crisis response needs a mental health component in a region with few services. (First author: verify.)

Hidden burden and costs of COVID-19 in South Asia — Owais (2023)

Objective: Measure how lockdowns disrupted essential health services in six South Asian countries and estimate resulting maternal and child deaths. Findings: Services dropped sharply in early 2020, recovered, then fell again in the 2021 Delta wave. Indirect maternal and child deaths likely exceeded the region's recorded COVID deaths. Hardest on the most vulnerable. Implications: Pandemic policy must protect essential services and target the poorest, or lockdowns cost more lives than the virus.

Prevalence of mental disorders in South Asia — Vidyasagaran (2023)

Objective: Estimate how common mental disorders and self-harm are in South Asia (review of reviews). Findings: Mental disorders and self-harm are highly prevalent in adults and vulnerable groups. Depression and anxiety estimates are substantial and vary by country and screening tool. Evidence on other conditions is thin. Implications: Large, under-measured burden with few resources. Better data needed to plan services.

Prevalence of common mental disorders in South Asia — Naveed (2020) [syllabus lists Safdar]

Objective: Estimate the pooled prevalence of common mental disorders across South Asia (meta-regression). Findings: South Asia reports among the highest prevalence in the world. Depression, anxiety, mixed anxiety-depression, and tobacco and alcohol use are most common. Bipolar, panic disorder and OCD are rarer. Implications: Need culturally appropriate interventions and more psychiatric research.

Mental health problems of adolescents in South Asia — Mudunna (2025)

Objective: Assess the types, prevalence and causes of mental health problems among South Asian adolescents (10–19). Findings: Problems are common, especially anxiety and depression in India and Pakistan. Risk factors: violence, poor family, home or school environments, peers, substance use. Protective: physical activity, nutrition, safe home, maternal education, schooling. Implications: Drivers are mostly social and economic, so policy must address social determinants in culturally fitting ways