A global systematic analysis of the occurrence, severity, and recovery pattern of long COVID in 2020 and 2021 (preprint)

ImportanceWhile 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. ObjectiveTo 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 DesignWe 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. ResultsAnalyses 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 relevanceThe 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 PointsO_ST_ABSQuestionC_ST_ABSWhat are the extent and nature of the most common long COVID symptoms by country in 2020 and 2021? FindingsGlobally, 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. MeaningThe 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.

Costs and Affordability of COVID-19 Testing and Treatment in India (preprint)

Background: The COVID-19 pandemic has triggered several underlying vulnerabilities with potentially far reaching consequences in low- and middle-income countries (LMICs) like India. Evidence of physical and socio-economic vulnerabilities caused by the pandemic are emerging rapidly, but one area that has received limited attention so far, is the financial vulnerability COVID-19 causes for households and the government. This paper aims to assess the financial burden imposed on governments and households and the ability of households to afford the required medical costs. Methods and FindingsUsing publicly available data, we computed per-episode mean costs for COVID-19 diagnosis and curative care by government and households. The curative costs included per-episode expenditure for (i) home isolation, (ii) hospital isolation and (i) ICU support. Expenditure was estimated based on mean costs derived from government capped package rates set for private facilities. Households’ affordability was assessed by comparing costs per episode to the estimated household income. The number of days required to pay for the cost of testing and treatment served as a proxy for households’ ability-to-pay. Work-days and wages/salaries for different types of workers were estimated based on Periodic Labor Force Surveys (PLFS, 2017-18) – a national level survey, with a sample size of 102,113 households and 433,339 persons, sampled through a stratified multi-stage random sampling approach. The mean cost for COVID-19 testing was Rs. 2,229 per test (Min-Max: Rs. 2200 – 2500) in a private facility and free in public facilities. The average cost of home isolation was Rs. 829 (Min-Max: Rs. 164 – 2743), while a 10-day episode of hospital isolation in a private facility was Rs. 67,470 (Min-Max: Rs. 2700 – 12600), and admission to the intensive care unit (ICU) cost Rs. 128,110 (Min-Max: Rs. 82500 – 200,000). To afford hospital isolation, regular employees would need to spend the equivalent of 124 days of wages while self-employed and casual workers would spend 170 days, and 257 days respectively. For ICU hospitalization, casual workers, regular employees, and self-employed workers would require 481 days, 318 days and 232 days of work respectively. Thus, affordability of COVID-19 services is far worse among casual workers, wherein annual wage falls short of ICU hospitalization cost for 90% of workers and hospital isolation costs for 48% of workers. Among self-employed workers, the proportions whose annual wages could not afford ICU hospitalization and home isolation were 66% and 27% respectively. For regular employees, we found that for 51% and 15% of them, their annual salaries could not afford to pay for ICU admission or hospital isolation respectively. ConclusionsBesides the financial burden associated with economic costs of COVID-19 lockdowns and other containment measures, the direct medical cost of seeking treatment by households is enormous and unsustainable. Our study has shown that households are subject to considerable financial burden rendering a sizeable segment unable to afford COVID-19 services. Future research must pay attention to measurements that can capture catastrophe and impoverishment inflicted by COVID-19 conditions. A deep dive to measure unaffordability must focus on what other basic needs are sacrificed while paying for COVID-19 conditions and treatments foregone.

The Cost of Procuring and Delivering COVID-19 Vaccines in Low- and Middle-Income Countries: A Model of Projected Resource Needs (preprint)

Background: Ending the COVID-19 pandemic requires effective implementation of vaccination programs in all countries. Information on the cost of vaccine procurement and delivery is paramount for effective planning and budgeting, especially in low- and middle-income countries (LMICs) given their budget constraints.Methods: We estimated regional and national costs to scale up COVID-19 vaccinations in 132 LMICs under different scenarios. We defined three priority groups: 1) healthcare workers; 2) population at high risk of severe COVID-19; and 3) adults with low risk of mortality and morbidity. We assumed that 70% of the population needs to be vaccinated to reach vaccine herd immunity. We used publicly available data on procurement pricing, delivery costs, and population size. We compared the price tag estimates to the countries’ historical annual immunization spending.Findings: We estimated a total cost of US$74 billion to reach vaccine herd immunity in LMICs. Of this total, 67% (US$50 billion) is for vaccine procurement, 33% (US$24 billion) is for vaccine delivery, 6% (US$4·2 billion) is to vaccinate high-risk populations, and 0.6% (US$0·46 billion) is to vaccinate healthcare workers. Twenty percent of LMICs have a price tag that is at least 10 times their baseline annual immunization spending.Interpretation: COVID-19 vaccination will have a major impact on LMIC national healthcare budgets. Substantial investments by governments and donors are needed for vaccine procurement and vaccine delivery infrastructure.Funding: Duke Global Health Institute pilot grant.Conflict of Interest: Dr. Dixit reports grants from Bill & Melinda Gates Foundation, outside the submitted work, all other authors have nothing to disclose.

Developing an Aggregator Mechanism for Late-Stage Clinical Trials of Neglected Disease Product Candidates (preprint)

There have been significant improvements in recent years in the early stage development of products for poverty-related and neglected diseases (PRNDs). However, there are still major challenges in the funding of late-stage clinical trials of candidate products for these diseases. For vaccine development specifically, Rappuoli and colleagues recently concluded that “these improvements in the early development process have revealed a new, and possibly more perilous, Valley of Death in the late vaccine development phase.” There are three major challenges in conducting phase III trials for PRND product development. First, such trials are expensive and companies often shy away from investing in them because there is no commercial market for most PRNDs. Second, there is poor coordination on late-stage trials across R&D initiatives. At present, there is no overarching global mechanism that is “steering the ship”—there is no universally agreed-upon process for prioritizing R&D investments for PRNDs, for selecting the most promising candidates, or for coordinating the multiple, overlapping research programs worldwide. The result is duplication, waste, and ultimately delays in the development of products. Third, current R&D efforts for PRNDs are “top-down”—they are controlled by high-income countries (HICs) and have generally done poorly at including decision-makers from high-burden countries. It is policymakers in low- and middle-income countries (LMICs) who are in the trenches when it comes to controlling PRNDs—yet they are often not at the table when it comes to deciding on what gets funded, where research is conducted, who gets access to intellectual property, and where and how the technologies end up being manufactured. All these steps need to be “globalized” if we are to develop and deploy new control tools.