Most downloaded biology preprints, all time
in category health policy
361 results found. For more information, click each entry to expand.
2,978 downloads medRxiv health policy
BackgroundHistorically, patients have had difficulty obtaining copies of their medical records, notwithstanding the legal right to do so. In 2018, a study of 83 top hospitals found discrepancies between those hospitals published information and telephone survey responses regarding their processes for release of records to patients, indicating noncompliance with the HIPAA right of individual access. ObjectiveAssess state of compliance with the HIPAA right of access across a broader range of health care providers and in the context of real records requests from patients. MethodsEvaluate the degree of compliance with the HIPAA right of access 1) through telephone surveys of health care institutions regarding release of records to patients and 2) by scoring the responses of a total of 210 health care providers to actual patient record requests against the HIPAA right of access requirements. (51 of those providers were part of an initial cohort of 51 scored for an earlier version of this paper.) ResultsBased on the scores of responses of 210 health care providers to record requests and the responses of nearly 3000 healthcare institutions to telephone surveys, more than 50% of health care providers are out of compliance with the HIPAA right of access. The most common failure was refusal to send records to patient or patients designee in the form and format requested by the patient, with 86% of noncompliance due to this factor. The number of phone calls required to obtain records in compliance with HIPAA, and the lack of consistency in provider responses to actual requests, makes the records retrieval process a challenging one for patients. ConclusionsRecent federal proposals prioritize patient access to medical records through certified electronic health record (EHR) technology, but access by patients to their complete clinical records via EHRs is years away. In the meantime, health care providers need to focus more attention on compliance with the HIPAA right of access, including better training of staff on HIPAA requirements. Greater enforcement of the law will help motivate providers to prioritize this issue.
2,948 downloads medRxiv health policy
The COVID-19 pandemic has taken a significant toll on nursing homes in the US, with upwards of a third of deaths occurring in nursing homes, and more in long-term care facilities. By combining data on facility-level COVID-19 deaths with facility-level data on the neighborhoods where nursing home staff reside for a sample of eighteen states, this paper finds that staff neighborhood characteristics are a large and significant predictor of COVID-19 outbreaks. One standard deviation increases in average staff tract population density, public transportation use, and non-white share were associated with 1.3 (SE .33), 1.4 (SE .35), and 0.9 (SE .24) additional deaths per 100 beds, respectively. These effects are larger than all facility management or quality variables, and larger than the effect of the nursing home's own neighborhood characteristics. These results suggest that staff communities are likely to be an important source of infection, and that disparities in nursing home outbreaks may be related to differences in the types of neighborhoods nursing home staff live in.
2,845 downloads medRxiv health policy
COVID-19 created a global public health and economic emergency. Policymakers acted quickly and decisively to contain the spread of disease through physical distancing measures. However, these measures also impact physical, mental and economic well-being, creating difficult trade-offs. Here we use a simple mathematical model to explore the balance between public health measures and their associated social and economic costs. Across a range of cost-functions and model structures, commitment to intermittent and strict social distancing measures leads to better overall outcomes than temporally consistent implementation of moderate physical distancing measures. With regard to the trade-offs that policymakers may soon face, our results emphasize that economic and health outcomes do not exist in full competition. Compared to consistent moderation, intermittently strict policies can better mitigate the impact of the pandemic on both of these priorities for a range of plausible utility functions.
2,811 downloads medRxiv health policy
Objectives Use of Personal Protective Equipment (PPE) has been central to controlling spread of SARS-CoV2. Here we quantify the environmental impact of PPE distributed for use by the health and social care system in England, and model strategies for mitigating the environmental impact. Methods Life cycle assessment was used to determine environmental impacts of PPE distributed to health and social care in England during the first six months of the COVID-19 pandemic. The base scenario assumed all products were single-use and disposed of via clinical waste. Scenario modelling was used to determine the effect of environmental mitigation strategies; 1) eliminating international travel during supply, 2) eliminating glove use 3) reusing gowns and face shields, 4) maximal recycling. Results The carbon footprint of PPE distributed during the study period totalled 106,478 tonnes CO2e, with greatest contributions from gloves, aprons, face shields, and Type IIR surgical masks. The estimated damage to human health was 239 DALYs (disability adjusted life years), impact on ecosystems was 0.47 species.year (loss of local species per year), and impact on resource depletion was costed at US $ 12.7 (GBP 9.3) million. Scenario modelling indicated UK manufacture would have reduced the carbon footprint by 12%, eliminating gloves by 45%, reusing gowns and gloves by 10%, and maximal recycling by 35%. A combination of strategies may have reduced carbon footprint by 75% compared with the base scenario, and saved an estimated 183 DALYS, 0.34 species.year, and US $ 7.4 (GBP 5.4) million due to resource depletion. Conclusions The environmental impact of PPE is large and could be reduced through domestic manufacture, rationalising glove use, using reusables where possible, and optimising waste management.
2,700 downloads medRxiv health policy
Objective Allocation of medical resource is essential to a strong public health system in response to COVID-19. Analysis of confirmed COVID-19 patients' hospital length of stay in Sichuan can be informative to decision-making in other regions of the world. Design A retrospective cross-sectional study. Data and Method Data from confirmed COVID-19 cases in Sichuan Province were obtained from the National Notifiable Diseases Reporting System (NNDRS) and field survey. We collected information on demographic, epidemiological, clinical characteristics, and the length of hospital stay for confirmed patients. We conducted an exploratory analysis using adjusted multivariate cox-proportional models. Participants A total of 538 confirmed patients of COVID-19 infection in Sichuan Province from January to March 2020. Outcome measure The length of hospital stay after admissions for confirmed patients. Results From January 16, 2020 to March 4, 2020, 538 human cases of COVID-19 infection were laboratory-confirmed, and were hospitalized for treatment. Among these, 271 (50%) were 45 years of age or above, 285 (53%) were male, 450 (84%) were considered as having mild symptoms. The median hospital length of stay was 19 days (interquartile range (IQR): 14-23, Range: 3-41). Adjusted multivariate analysis showed that longer hospital length of stay was associated with factors aged 45 and over (HR: 0.74, 95% CI: 0.60-0.91), those admitted to provincial hospital (HR: 0.73, 95% CI: 0.54-0.99), and those with serious illness (HR: 0.66, 95% CI: 0.48-0.90); living in areas with more than 5.5 healthcare workers per 1000 population (HR: 1.32, 95% CI: 1.05-1.65) was associated with shorter hospital length of stay. There was no gender difference. Conclusions Preparation control measures of COVID-19 should involve the allocation of sufficient medical resources, especially in areas with older vulnerable populations and in areas that lack basic medical resources.
2,664 downloads medRxiv health policy
This note provides an early assessment of the reinforced measures to curb the COVID-19 pandemic in France, which include a curfew of selected areas and culminate in a second COVID-19-related lock-down that started on October 30, 2020 and is still ongoing. We analyse the change in virus propagation across age groups and across departements using an acceleration index introduced in Baunez et al. (2020). We find that while the pandemic is still in the acceleration regime, acceleration decreased notably with curfew measures and this more rapidly so for the more vulnerable population group, that is, for people older than 60. Acceleration continued to decline under lock-down, but more so for the active population under 60 than for those above 60. For the youngest population aged 0 to 19, curfew measures did not reduce acceleration but lock-down does. This suggests that if health policies aim at protecting the elderly population generally more at risk to suffer severe consequences from COVID-19, curfew measures may be effective enough. However, looking at the departmental map of France, we find that curfews have not necessarily been imposed in departements where acceleration was the largest. JEL Classification NumbersI18; H12
2,616 downloads medRxiv health policy
Relying on national official reports to assess the impact of COVID-19 pandemic on human life faces problems of miscounting due to under-reporting of COVID-19 deaths, inaccurate death registration and inconsistency in classification. The reported mortality is often provided at the national level whilst the outbreaks are localised, resulting in underestimation of the true scale of the impact. This study uses all-cause daily death registrations data provided by the Italian Statistical Office (ISTAT) focusing on the five most severely hit provinces in Italy (Bergamo, Brescia, Cremona, Lodi and Piacenza) and Lombardy region. We calculate excess mortality in 2020 compared to the average of the years 2015-2019 and estimate life expectancy for the first wave of the epidemic and for the rest of the year 2020. The estimated excess deaths show significantly higher mortality than official statistics, particularly during the peak of the epidemic and amongst people aged [≥]70 years. For the first wave of the epidemic (1 January to 30 April 2020), life expectancy in the five provinces reduced by 6.2 to 8 and 3.6 to 5.8 years for men and women, respectively. For annual life expectancy in 2020, with regular after-COVID mortality patterns, the years of life lost is equivalent to 2.5 to 4.1 years for men and 1.7. to 2.6 years for women, respectively.
2,534 downloads medRxiv health policy
Introduction: Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories. Methods: We used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission with data from January - June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs. Results: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g., restrictions on 1000+ people gathering were not effective, restrictions on <10 people gathering was). Evidence supporting the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Conclusion: Understanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications taking into account these effects, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many although not all the actions policy-makers are taking to respond to the COVID-19 pandemic.
2,439 downloads medRxiv health policy
Background and ObjectivesThe SARS-CoV2 pandemic has lead to a global decrease in protection ware, especially facepiece filtering respirators (FFRs). Ultraviolet-C wavelength is a promising way of descontamination, however adequate dosimetry is needed to ensure balance between over and underexposed areas and provide reliable results. Our study demonstrates that UVGI light dosage varies significantly on different respirator angles, and propose a method to descontaminate several masks at once ensuring appropriate dosage in shaded zones. MethodsAn UVGI irradiator was built with internal dimensions of 69.5 x55 x 33 cm with three 15W UV lamps. Inside, a grating of 58 x 41 x 15 cm was placed to hold the masks. Two different respirator models were used to assess irradiance, four of model Aura 9322 3M of dimensions 17 x 9 x 4cm, and two of model SAFE 231FFP3NR with dimensions 17 x 6 x 5 cm. A spectrometer STN-SilverNova was employed to verify wavelength spectrum and surface irradiance. A simulation was performed to find the irradiance pattern inside the box and the six masks placed inside. These simulations were carried out using the software DIALUX EVO 8.2. ResultsThe data obtained reveal that the dosage received inside the manufactured UVGI-irradiator depends not only on the distance between the luminaires plane and the base of the respirators but also on the orientation and shape of the masks. This point becomes relevant in order to assure that all the respirators inside the chamber receive the correct dosage. ConclusionIrradiance over FFR surfaces depend on several factors such as distance, angle of incidence of the light source. Careful dosage measurement and simulation can ensure reliable dosage in the whole mask surface, balancing overexposure. Closed box systems might provide a more reliable, reproducible UVGI dosage than open settings.
2,265 downloads medRxiv health policy
The development of a viable COVID-19 vaccine is a work in progress, but the success of the immunization campaign will depend upon public acceptance. In this paper, we classify Twitter users in COVID-19 discussion into vaccine refusers (anti-vaxxers) and vaccine adherers (vaxxers) communities. We study the divide between anti-vaxxers and vaxxers in the context of whom they follow. More specifically, we look at followership of 1) the U.S. Congress members, 2) four major religions (Christianity, Hinduism, Judaism and Islam), 3) accounts related to the healthcare community, and 4) news media accounts. Our results indicate that there is a partisan divide between vaxxers and anti-vaxxers. We find a religious community with a higher than expected fraction of anti-vaxxers. Further, we find that the variance of vaccine belief within the news media accounts operated by Russian and Iranian governments is higher compared to news media accounts operated by other governments. Finally, we provide messaging and policy implications to inform the COVID-19 vaccine and future vaccination plans.
2,247 downloads medRxiv health policy
COVID-19 Statistics, Policy modeling and Epidemiology Collective (C-SPEC), Alyssa Bilinski, Ruthie Birger, Samantha Burn, Melanie Chitwood, Emma Clarke-Deelder, Tyler Copple, Jeffrey Eaton, Hanna Ehrlich, Margret Erlendsdottir, Soheil Eshghi, Monica Farid, Meagan Fitzpatrick, John Giardina, Gregg Gonsalves, Yuli Lily Hsieh, Suzan Iloglu, Yu-Han Kao, Evan MacKay, Nick Menzies, Bianca Mulaney, David Paltiel, Stephanie Perniciaro, Maile Phillips, Katherine Rich, Joshua A Salomon, Raphael Sherak, Kayoko Shioda, Nicole Swartwood, Christian Testa, Thomas Thornhill, Elizabeth White, Anne Williamson, Anna York, Jinyi Zhu, Lin Zhu
Initial projections from the first generation of COVID-19 models focused public attention on worst-case scenarios in the absence of decisive policy action. These underscored the imperative for strong and immediate measures to slow the spread of infection. In the coming weeks, however, as policymakers continue enlisting models to inform decisions on COVID-19, answers to the most difficult and pressing policy questions will be much more sensitive to underlying uncertainties. In this study, we demonstrate a model-based approach to assessing the potential value of reducing critical uncertainties most salient to COVID-19 decision-making and discuss priorities for acquiring new data to reduce these uncertainties. We demonstrate how information about the impact of non-pharmaceutical interventions could narrow prediction intervals around hospitalizations over the next few weeks, while information about the prevalence of undetected cases could narrow prediction intervals around the timing and height of the peak of the epidemic.
2,146 downloads medRxiv health policy
Background Despite measures such as travel restrictions and lockdowns, the novel coronavirus (SARS-COV-2) is projected to spread across India. Considering that a vaccine for COVID-19 is will not be available soon, it is important to identify populations with high risk from COVID-19 and take measures to prevent outbreaks and build healthcare infrastructure at the local level. Methods We used data from two large nationally representative household surveys, administrative sources, and published studies to estimate the risk of COVID-19 at the district level in India. We employed principal component analysis to create an index of the health risk of COVID-19 from demographic and comorbidity indicators such as the proportions of elderly population and rates of diabetes, hypertension, and respiratory illnesses. Another principal component index examined the socioeconomic and healthcare access risk from COVID-19, based on the standard of living, proportion of caste groups, and per capita access to public healthcare in each district. Results Districts in northern, southern and western Indian states such as Punjab, Tamil Nadu, Kerala, and Maharashtra were at the highest health risk from COVID-19. Many of these districts have been designated as COVID-19 hotspots by the Indian government because of emergent outbreaks. Districts in eastern and central states such as Uttar Pradesh, Bihar, and Madhya Pradesh have higher socioeconomic and healthcare access risk as compared with other areas. Interpretation Districts at high risk of COVID-19 should prioritize policy measures for preventing outbreaks, and improving critical care infrastructure and socioeconomic safety nets.
2,102 downloads medRxiv health policy
Noah A Haber, Emma Clarke-Deelder, Avi Feller, Emily R. Smith, Joshua A Salomon, Benjamin MacCormack-Gelles, Elizabeth M Stone, Clara Bolster-Foucault, Jamie R Daw, Laura A. Hatfield, Carrie E Fry, Christopher B Boyer, Eli Ben-Michael, Caroline M Joyce, Beth S Linas, Ian Schmid, Eric H Au, Sarah E Wieten, Brooke A. Jarrett, Cathrine Axfors, Van Thu Nguyen, Beth Ann Griffin, Alyssa Bilinski, Elizabeth A Stuart
Introduction: Assessing the impact of COVID-19 policy is critical for informing future policies. However, there are concerns about the overall strength of COVID-19 impact evaluation studies given the circumstances for evaluation and concerns about the publication environment. This study systematically reviewed the strength of evidence in the published COVID-19 policy impact evaluation literature. Methods: We included studies that were primarily designed to estimate the quantitative impact of one or more implemented COVID-19 policies on direct SARS-CoV-2 and COVID-19 outcomes. After searching PubMed for peer-reviewed articles published on November 26 or earlier and screening, all studies were reviewed by three reviewers first independently and then to consensus. The review tool was based on previously developed and release review guidance for COVID-19 policy impact evaluation, assessing what impact evaluation method was used, graphical display of outcomes data, functional form for the outcomes, timing between policy and impact, concurrent changes to the outcomes, and an overall rating. Results: After 102 articles were identified as potentially meeting inclusion criteria, we identified 36 published articles that evaluated the quantitative impact of COVID-19 policies on direct COVID-19 outcomes. The majority (n=23/36) of studies in our sample examined the impact of stay-at-home requirements. Nine studies were set aside because the study design was considered inappropriate for COVID-19 policy impact evaluation (n=8 pre/post; n=1 cross-section), and 27 articles were given a full consensus assessment. 20/27 met criteria for graphical display of data, 5/27 for functional form, 19/27 for timing between policy implementation and impact, and only 3/27 for concurrent changes to the outcomes. Only 1/27 studies passed all of the above checks, and 4/27 were rated as overall appropriate. Including the 9 studies set aside, reviewers found that only four of the 36 identified published and peer-reviewed health policy impact evaluation studies passed a set of key design checks for identifying the causal impact of policies on COVID-19 outcomes. Discussion: The reviewed literature directly evaluating the impact of COVID-19 policies largely failed to meet key design criteria for useful inference. This was largely driven by the circumstances under which policies were passed making it difficult to attribute changes in COVID-19 outcomes to particular policies. More reliable evidence review is needed to both identify and produce policy-actionable evidence, alongside the recognition that actionable evidence is often unlikely to be feasible.
1,964 downloads medRxiv health policy
BackgroundThe coronavirus disease-19 (COVID-19) pandemic threatens to overwhelm the healthcare resources of the country, but also poses a personal hazard to healthcare workers, including physicians. To address the potential impact of excluding physicians with a high risk of adverse outcomes based on age, we evaluated the current patterns of age of licensed physicians across the United States. MethodsWe compiled information from the 2018 database of actively licensed physicians in the Federation of State Medical Boards (FSMB) across the US. Both at a national- and the state-level, we assessed the number and proportion of physicians who would be at an elevated risk due to age over 60 years. ResultsOf the 985,026 licensed physicians in the US, 235857 or 23.9% were aged 25-40 years, 447052 or 45.4% are 40-60 years, 191794 or 19.5% were 60-70 years, and 106121 or 10.8% were 70 years or older. Age was not reported in 4202 or 0.4% of physicians. Overall, 297915 or 30.2% of physicians were 60 years of age or older, 246167 (25.0%) 65 years and older, and 106121 (10.8%) 70 years or older. States in the US reported that a median 5470 licensed physicians (interquartile range [IQR], 2394 to 10108) were 60 years of age or older. Notably, states of North Dakota (n=1180) and Vermont (n = 1215) had the lowest and California (n=50786) and New York (n=31582) the highest number of physicians over the age of 60 years (Figure 1). Across states, the median proportion of physicians aged 60 years and older was 28.9% (IQR, 27.2%, 31.4%), and ranged between 25.9% for Nebraska to 32.6% for New Mexico (Figure 2). DiscussionOlder physicians represent a large proportion of the US physician workforce, particularly in states with the worst COVID-19 outbreak. Therefore, their exclusion from patient care will be impractical. Optimizing care practices by limiting direct patient contact of physicians vulnerable to adverse outcomes from COVID-19, potentially by expanding their participation in telehealth may be a strategy to protect them.
1,929 downloads medRxiv health policy
In order to control the spread of infectious diseases such as COVID-19, it will be important to develop a communication strategy to counteract "vaccine hesitancy". This paper reports the results of a survey experiment testing the impacts of several types of message content: the safety and efficacy of the vaccine itself, the likelihood that others will take the vaccine, and the possible role of politics in promoting the vaccine. In an original survey of 1123 American M-Turk respondents, we provided six different information conditions suggesting the safety and efficacy of the vaccine, the lack of safety/efficacy of the vaccine, the suggestion that most others would take the vaccine, the suggestion that most others would not take the vaccine, the suggestion that the vaccine is being promoted to gain greater control over individual freedom, and the suggestion that it is being rushed for political motivations. We compared the responses for those in the treatment groups with a control group who received no additional information. In comparison to the control group, those who received information about the safety/efficacy of the vaccine were more likely to report that they would take the vaccine, those who received information that others were reluctant to take the vaccine were more likely to report that they themselves would not take it, that other Americans would not take it, and that it was not important to get the vaccine, and those who received information about political influences on vaccine development expressed hesitancy to take it. Communication of effective messages about the vaccine will be essential for public health agencies that seek to promote vaccine take-up.
1,803 downloads medRxiv health policy
We show that large declines in maternal mortality can be achieved by raising womens political participation. We estimate that the recent wave of quotas for women in parliament in low income countries has resulted in a 9 to 12% decline in maternal mortality. Among mechanisms are that gender quotas lead to an 8 to 10% increase in skilled birth attendance, a 6 to 12% increase in prenatal care utilization and a 4 to 11% decrease in birth rates. JEL codesI14, I15, O15.
1,777 downloads medRxiv health policy
Kerala reported the first three cases of coronavirus in India in late January. Kerala, one of Indias most densely populated states, which makes its success in fighting the Covid-19 all the more commendable. Moreover, an estimated 17% of its 35 million population employed or lives elsewhere, more than 1 million tourists visit each year, and hundreds of students study abroad, including in China. All of this mobility makes the state more vulnerable to contagious outbreaks. What is the strategy behind the success story? This paper compares the situation of COVID-19 pandemic in major states and Kerala by the different phase of lockdown, and also highlights Keralas fight against the pandemic. We used publicly available data from https://www.covid19india.org/ and Covid-19 Daily Bulletin (Jan 31-May 31), Directorate of Health Services, Kerala (https://dashboard.kerala.gov.in/). We calculate the phase-wise period prevalence rate (PPR) and the case fatality rate (CFR) of the last phase. Compared to other major states, Kerala showed better response in preventing pandemic. The equation for the Keralas success has been simple, prioritized testing, widespread contact tracing, and promoting social distance. They also imposed uncompromising controls, that were supported by an excellent healthcare system, government accountability, transparency, public trust, civil rights and importantly the decentralized governance and strong grass-root level institutions. The proactive measures taken by Kerala such as early detection of cases and extensive social support measures can be a model for India and the world. Keywords: Covid-19, Kerala, India, Testing, Tracing, Pandemic.
1,775 downloads medRxiv health policy
As COVID-19 vaccines are rolled out across the world, there are growing concerns about the role that trust, belief in conspiracy theories and spread of misinformation through social media impact vaccine hesitancy. We use a nationally representative survey of 1,476 adults in the UK between December 12 to 18, 2020 and five focus groups conducted in the same period. Trust is a core predictor, with distrust in vaccines in general and mistrust in government raising vaccine hesitancy. Trust in health institutions and experts and perceived personal threat are vital, with focus groups revealing that COVID-19 vaccine hesitancy is driven by a misunderstanding of herd immunity as providing protection, fear of rapid vaccine development and side effects, belief the virus is man-made and related to population control. Particularly those who obtain information from relatively unregulated social media sources such as YouTube that have recommendations tailored by watch history are less likely to be willing to become vaccinated. Those who hold general conspiratorial beliefs are less willing to be vaccinated. Since an increasing number of individuals use social media for gathering health information, interventions require action from governments, health officials and social media companies. More attention needs to help people understand their own risks, unpack complex concepts and fill knowledge voids.
1,680 downloads medRxiv health policy
To reliably estimate the demand on regional health systems and perform public health planning, it is necessary to have a good estimate of the prevalence of infection with SARS-CoV-2 (the virus that causes COVID-19) in the population. In the absence of wide-spread testing, we provide one approach to infer prevalence based on the assumption that the fraction of true infections needing hospitalization is fixed and that all hospitalized cases of COVID-19 in Santa Clara are identified. Our goal is to estimate the prevalence of SARS-CoV-2 infections, i.e. the true number of people currently infected with the virus, divided by the total population size. Our analysis suggests that as of March 17, 2020, there are 6,500 infections (0.34% of the population) of SARS-CoV-2 in Santa Clara County. Based on adjusting the parameters of our model to be optimistic (respectively pessimistic), the number of infections would be 1,400 (resp. 26,000), corresponding to a prevalence of 0.08% (resp. 1.36%). If the shelter-in-place led to R0 < 1, we would expect the number of infections to remain about constant for the next few weeks. However, even if this were true, we expect to continue to see an increase in hospitalized cases of COVID-19 in the short term due to the fact that infection of SARS-CoV-2 on March 17th can lead to hospitalizations up to 14 days later.
1,551 downloads medRxiv health policy
The outbreak of COVID-19 has spurred extensive research worldwide to develop a vaccine. However, when a vaccine becomes available, limited production and distribution capabilities will likely lead to another challenge: who to prioritize for vaccination to mitigate the near-end impact of the pandemic? To tackle that question, this paper first expands a state-of-the-art epidemiological model, called DELPHI, to capture the effects of vaccinations and the variability in mortality rates across subpopulations. It then integrates this predictive model into a prescriptive model to optimize vaccine allocation, formulated as a bilinear, non-convex optimization model. To solve it, this paper proposes a coordinate descent algorithm that iterates between optimizing vaccine allocations and simulating the dynamics of the pandemic. We implement the model and algorithm using real-world data in the United States. All else equal, the optimized vaccine allocation prioritizes states with a large number of projected cases and sub-populations facing higher risks (e.g., older ones). Ultimately, the optimized vaccine allocation can reduce the death toll of the pandemic by an estimated 10-25%, or 10,000-20,000 deaths over a three-month period in the United States alone. Highlights- This paper formulates an optimization model for vaccine allocation in response to the COVID-19 pandemic. This model, referred to as DELPHI-V-OPT, integrates a predictive epidemiological model into a prescriptive model to support the allocation of vaccines across geographic regions (e.g., US states) and across risk classes (e.g., age groups). - This paper develops a scalable coordinate descent algorithm to solve the DELPHI-V-OPT model. The proposed algorithm converges effectively and in short computational times. Therefore, the proposed approach can be implemented efficiently, and allows extensive sensitivity analyses for scenario planning and policy analysis. - Computational results demonstrate that optimized vaccine allocation strategies can curb the death toll of the COVID-19 pandemic by an estimated at 10-25%, or 10,000-20,000 deaths over a three-month period in the United States alone. These results highlight the critical role of vaccine allocation to combat the COVID-19 pandemic, in addition to vaccine design and vaccine production.
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