Background Development assistance for health (DAH) is an important source of financing for health for many low-income and some middle-income countries. Most DAH has predominantly been contributed by high-income countries. However, in the context of economic progress and changing global priorities, DAH contributions from countries of the Global South such as India have gained importance. In this paper, we estimate DAH contributed by India between 2009 and 2020. Methods We leveraged data from budgetary documents, databases, and financial reports of the Ministry of External Affairs and multilateral organizations to estimate DAH contributions. The proportions of development assistance that go towards health in major recipient countries were estimated and reported by recipient country and year. Results Between 2009 and 2020, DAH contributed by India to bilateral and multilateral partners totaled $206.0 million. South Asian countries including Bangladesh, Bhutan, Nepal, Sri Lanka, and Myanmar received the most DAH from India. DAH contributed relative to DAH received ranged from 1.42% in 2009 to 5.26% in 2018, the latest year with country-level data. Health focus areas prioritized by India included technical training and innovation, health care infrastructure support, and supply of medications and medical equipment. Conclusion India is an important development partner to many countries-particularly to those in the South Asian region. India's DAH allocation strategy prioritizes contributions toward neighboring countries in the South Asia region in several health focus areas. Detailed project-level data are needed to estimate DAH contributions from India with greater precision and accuracy.

IMPORTANCE Some individuals experience persistent symptoms after initial symptomatic SARS-CoV-2 infection (often referred to as Long COVID). OBJECTIVE To estimate the proportion of males and females with COVID-19, younger or older than 20 years of age, who had Long COVID symptoms in 2020 and 2021 and their Long COVID symptom duration. DESIGN, SETTING, AND PARTICIPANTS Bayesian meta-regression and pooling of 54 studies and 2 medical record databases with data for 1.2 million individuals (from 22 countries) who had symptomatic SARS-CoV-2 infection. Of the 54 studies, 44 were published and 10 were collaborating cohorts (conducted in Austria, the Faroe Islands, Germany, Iran, Italy, the Netherlands, Russia, Sweden, Switzerland, and the US). The participant data were derived from the 44 published studies (10 501 hospitalized individuals and 42 891 nonhospitalized individuals), the 10 collaborating cohort studies (10 526 and 1906), and the 2 US electronic medical record databases (250 928 and 846 046). Data collection spanned March 2020 to January 2022. EXPOSURES Symptomatic SARS-CoV-2 infection. MAIN OUTCOMES AND MEASURES Proportion of individuals with at least 1 of the 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after SARS-CoV-2 infection in 2020 and 2021, estimated separately for hospitalized and nonhospitalized individuals aged 20 years or older by sex and for both sexes of nonhospitalized individuals younger than 20 years of age. RESULTS A total of 1.2 million individuals who had symptomatic SARS-CoV-2 infection were included (mean age, 4-66 years; males, 26%-88%). In the modeled estimates, 6.2% (95% uncertainty interval [UI], 2.4%-13.3%) of individuals who had symptomatic SARS-CoV-2 infection experienced at least 1 of the 3 Long COVID symptom clusters in 2020 and 2021, including 3.2% (95% UI, 0.6%-10.0%) for persistent fatigue with bodily pain or mood swings, 3.7% (95% UI, 0.9%-9.6%) for ongoing respiratory problems, and 2.2% (95% UI, 0.3%-7.6%) for cognitive problems after adjusting for health status before COVID-19, comprising an estimated 51.0% (95% UI, 16.9%-92.4%), 60.4% (95% UI, 18.9%-89.1%), and 35.4% (95% UI, 9.4%-75.1%), respectively, of Long COVID cases. The Long COVID symptom clusters were more common in women aged 20 years or older (10.6% [95% UI, 4.3%-22.2%]) 3 months after symptomatic SARS-CoV-2 infection than in men aged 20 years or older (5.4% [95% UI, 2.2%-11.7%]). Both sexes younger than 20 years of age were estimated to be affected in 2.8% (95% UI, 0.9%-7.0%) of symptomatic SARS-CoV-2 infections. The estimated mean Long COVID symptom cluster duration was 9.0 months (95% UI, 7.0-12.0 months) among hospitalized individuals and 4.0 months (95% UI, 3.6-4.6 months) among nonhospitalized individuals. Among individuals with Long COVID symptoms 3 months after symptomatic SARS-CoV-2 infection, an estimated 15.1% (95% UI, 10.3%-21.1%) continued to experience symptoms at 12 months. CONCLUSIONS AND RELEVANCE This study presents modeled estimates of the proportion of individuals with at least 1 of 3 self-reported Long COVID symptom clusters (persistent fatigue with bodily pain or mood swings; cognitive problems; or ongoing respiratory problems) 3 months after symptomatic SARS-CoV-2 infection.

Importance:While much of the attention on the COVID-19 pandemic was directed at the daily counts of cases and those with serious disease overwhelming health services, increasingly, reports have appeared of people who experience debilitating symptoms after the initial infection. This is popularly known as long COVID. Objective:To estimate by country and territory of the number of patients affected by long COVID in 2020 and 2021, the severity of their symptoms and expected pattern of recovery. Design:We jointly analyzed ten ongoing cohort studies in ten countries for the occurrence of three major symptom clusters of long COVID among representative COVID cases. The defining symptoms of the three clusters (fatigue, cognitive problems, and shortness of breath) are explicitly mentioned in the WHO clinical case definition. For incidence of long COVID, we adopted the minimum duration after infection of three months from the WHO case definition. We pooled data from the contributing studies, two large medical record databases in the United States, and findings from 44 published studies using a Bayesian meta-regression tool. We separately estimated occurrence and pattern of recovery in patients with milder acute infections and those hospitalized. We estimated the incidence and prevalence of long COVID globally and by country in 2020 and 2021 as well as the severity-weighted prevalence using disability weights from the Global Burden of Disease study. Results:Analyses are based on detailed information for 1906 community infections and 10526 hospitalized patients from the ten collaborating cohorts, three of which included children. We added published data on 37262 community infections and 9540 hospitalized patients as well as ICD-coded medical record data concerning 1.3 million infections. Globally, in 2020 and 2021, 144.7 million (95% uncertainty interval [UI] 54.8-312.9) people suffered from any of the three symptom clusters of long COVID. This corresponds to 3.69% (1.38-7.96) of all infections. The fatigue, respiratory, and cognitive clusters occurred in 51.0% (16.9-92.4), 60.4% (18.9-89.1), and 35.4% (9.4-75.1) of long COVID cases, respectively. Those with milder acute COVID-19 cases had a quicker estimated recovery (median duration 3.99 months [IQR 3.84-4.20]) than those admitted for the acute infection (median duration 8.84 months [IQR 8.10-9.78]). At twelve months, 15.1% (10.3-21.1) continued to experience long COVID symptoms. Conclusions and relevance:The occurrence of debilitating ongoing symptoms of COVID-19 is common. Knowing how many people are affected, and for how long, is important to plan for rehabilitative services and support to return to social activities, places of learning, and the workplace when symptoms start to wane. Key Points:Question: What are the extent and nature of the most common long COVID symptoms by country in 2020 and 2021?Findings: Globally, 144.7 million people experienced one or more of three symptom clusters (fatigue; cognitive problems; and ongoing respiratory problems) of long COVID three months after infection, in 2020 and 2021. Most cases arose from milder infections. At 12 months after infection, 15.1% of these cases had not yet recovered.Meaning: The substantial number of people with long COVID are in need of rehabilitative care and support to transition back into the workplace or education when symptoms start to wane.

Background The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. Methods We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. Findings In 2019, health spending globally reached $8. 8 trillion (95% uncertainty interval [UI] 8.7-8.8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this total, $40.4 billion (0.5%, 95% UI 0.5-0.5) was development assistance for health provided to low-income and middle-income countries, which made up 24.6% (UI 24.0-25.1) of total spending in low-income countries. We estimate that $54.8 billion in development assistance for health was disbursed in 2020. Of this, $13.7 billion was targeted toward the COVID-19 health response. $12.3 billion was newly committed and $1.4 billion was repurposed from existing health projects. $3.1 billion (22.4%) of the funds focused on country-level coordination and $2.4 billion (17.9%) was for supply chain and logistics. Only $714.4 million (7.7%) of COVID-19 development assistance for health went to Latin America, despite this region reporting 34.3% of total recorded COVID-19 deaths in low-income or middle-income countries in 2020. Spending on health is expected to rise to $1519 (1448-1591) per person in 2050, although spending across countries is expected to remain varied. Interpretation Global health spending is expected to continue to grow, but remain unequally distributed between countries. We estimate that development organisations substantially increased the amount of development assistance for health provided in 2020. Continued efforts are needed to raise sufficient resources to mitigate the pandemic for the most vulnerable, and to help curtail the pandemic for all. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.

Introduction In 2017, development assistance for health (DAH) comprised 5.3% of total health spending in low-income countries. Despite the key role DAH plays in global health-spending, little is known about the characteristics of assistance that may be associated with committed assistance that is actually disbursed. In this analysis, we examine associations between these characteristics and disbursement of committed assistance. Methods We extracted data from the Creditor Reporting System of the Organization for Economic Co-operation and Development, Institute for Health Metrics and Evaluation, and the WHO National Health Accounts database. Factors examined were off-budget assistance, administrative assistance, publicly sourced assistance and assistance to health systems strengthening. Recipient-country characteristics examined were perceived level of corruption, civil fragility and gross domestic product per capita (GDPpc). We used linear regression methods for panel of data to assess the proportion of committed aid that was disbursed for a given country-year, for each data source. Results Factors that were associated with a higher disbursement rates include off-budget aid (p<0.001), lower administrative expenses (p<0.01), lower perceived corruption in recipient country (p<0.001), lower fragility in recipient country (p<0.05) and higher GDPpc (p<0.05). Conclusion Substantial gaps remain between commitments and disbursements. Characteristics of assistance (administrative, publicly sourced) and indicators of government transparency and fragility are also important drivers associated with disbursement of DAH. There remains a continued need for better aid flow reporting standards and clarity around aid types for better measurement of DAH.

Background Sustainable Development Goal (SDG) 3 aims to "ensure healthy lives and promote well-being for all at all ages". While a substantial effort has been made to quantify progress towards SDG3, less research has focused on tracking spending towards this goal. We used spending estimates to measure progress in financing the priority areas of SDG3, examine the association between outcomes and financing, and identify where resource gains are most needed to achieve the SDG3 indicators for which data are available. Methods We estimated domestic health spending, disaggregated by source (government, out-of-pocket, and prepaid private) from 1995 to 2017 for 195 countries and territories. For disease-specific health spending, we estimated spending for HIV/AIDS and tuberculosis for 135 low-income and middle-income countries, and malaria in 106 malaria-endemic countries, from 2000 to 2017. We also estimated development assistance for health (DAH) from 1990 to 2019, by source, disbursing development agency, recipient, and health focus area, including DAH for pandemic preparedness. Finally, we estimated future health spending for 195 countries and territories from 2018 until 2030. We report all spending estimates in inflation-adjusted 2019 US$, unless otherwise stated. Findings Since the development and implementation of the SDGs in 2015, global health spending has increased, reaching $7.9 trillion (95% uncertainty interval 7.8-8.0) in 2017 and is expected to increase to $11.0 trillion (10.7-11.2) by 2030. In 2017, in low-income and middle-income countries spending on HIV/AIDS was $20.2 billion (17.0-25.0) and on tuberculosis it was $10.9 billion (10.3-11.8), and in malaria-endemic countries spending on malaria was $5.1 billion (4.9-5.4). Development assistance for health was $40.6 billion in 2019 and HIV/AIDS has been the health focus area to receive the highest contribution since 2004. In 2019, $374 million of DAH was provided for pandemic preparedness, less than 1% of DAH. Although spending has increased across HIV/AIDS, tuberculosis, and malaria since 2015, spending has not increased in all countries, and outcomes in terms of prevalence, incidence, and per-capita spending have been mixed. The proportion of health spending from pooled sources is expected to increase from 81.6% (81.6-81.7) in 2015 to 83.1% (82.8-83.3) in 2030. Interpretation Health spending on SDG3 priority areas has increased, but not in all countries, and progress towards meeting the SDG3 targets has been mixed and has varied by country and by target. The evidence on the scale-up of spending and improvements in health outcomes suggest a nuanced relationship, such that increases in spending do not always results in improvements in outcomes. Although countries will probably need more resources to achieve SDG3, other constraints in the broader health system such as inefficient allocation of resources across interventions and populations, weak governance systems, human resource shortages, and drug shortages, will also need to be addressed. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.