Indirect vaccine effectiveness in an outbreak of Alpha B.1.1.7 variant in a California state Prison, May 2021.

Incarcerated populations experienced high rates of SARS-CoV-2 infection and death during early phases of the COVID-19 pandemic. To evaluate vaccine effectiveness in the carceral context, we investigated the first outbreak of COVID-19 in a California state prison following widespread rollout of vaccines to residents in early 2021. We identified a cohort of 733 state prison residents presumed to be exposed between May 14 and June 22, 2021. 46.9 % (n = 344) were vaccinated, primarily with two doses of mRNA-1273 (n = 332, 93.6 %). In total, 92 PCR-positive cases were identified, of which 14 (14.5 %) occurred among mRNA-1273 vaccinated residents. No cases required hospitalization. All nine isolates collected belonged to the Alpha (B.1.1.7) variant. We used Cox proportional hazard regression to estimate vaccine effectiveness for at least one dose of any vaccine at the start of the outbreak. Vaccine effectiveness was 86 % (95 % CI: 75 %-97 %) against PCR-confirmed infection, with similar results for symptomatic infection. Higher rates of building-level vaccine uptake were associated with a lower overall rate of PCR-confirmed infection and symptomatic infection among unvaccinated residents. Among unvaccinated residents who lived in shared cells at the time of presumed exposure, exposure to a vaccinated cellmate was associated with a 38% (95% CI: 0.37, 1.04) lower hazard rate of PCR-confirmed infection over the study period. In this outbreak involving the Alpha SARS-CoV-2 variant, vaccination conferred direct and possibly indirect protection against SARS-CoV-2 infection and symptomatic COVID-19. Our results support the importance of vaccine uptake in mitigating outbreaks and severe disease in the prison setting and the consideration of community vaccination levels in policy and infection response.

SARS-CoV-2 infection by trimester of pregnancy and adverse perinatal outcomes: a Mexican retrospective cohort study.

OBJECTIVE: Conflicting evidence for the association between COVID-19 and adverse perinatal outcomes exists. This study examined the associations between maternal COVID-19 during pregnancy and adverse perinatal outcomes including preterm birth (PTB), low birth weight (LBW), small-for-gestational age (SGA), large-for-gestational age (LGA) and fetal death; as well as whether the associations differ by trimester of infection. DESIGN AND SETTING: The study used a retrospective Mexican birth cohort from the Instituto Mexicano del Seguro Social (IMSS), Mexico, between January 2020 and November 2021. PARTICIPANTS: We used the social security administrative dataset from IMSS that had COVID-19 information and linked it with the IMSS routine hospitalisation dataset, to identify deliveries in the study period with a test for SARS-CoV-2 during pregnancy. OUTCOME MEASURES: PTB, LBW, SGA, LGA and fetal death. We used targeted maximum likelihood estimators, to quantify associations (risk ratio, RR) and CIs. We fit models for the overall COVID-19 sample, and separately for those with mild or severe disease, and by trimester of infection. Additionally, we investigated potential bias induced by missing non-tested pregnancies. RESULTS: The overall sample comprised 17 340 singleton pregnancies, of which 30% tested positive. We found that those with mild COVID-19 had an RR of 0.89 (95% CI 0.80 to 0.99) for PTB and those with severe COVID-19 had an RR of 1.53 (95% CI 1.07 to 2.19) for LGA. COVID-19 in the first trimester was associated with fetal death, RR=2.36 (95% CI 1.04, 5.36). Results also demonstrate that missing non-tested pregnancies might induce bias in the associations. CONCLUSIONS: In the overall sample, there was no evidence of an association between COVID-19 and adverse perinatal outcomes. However, the findings suggest that severe COVID-19 may increase the risk of some perinatal outcomes, with the first trimester potentially being a high-risk period.

Estimating the effect of realistic improvements of metformin adherence on COVID-19 mortality using targeted machine learning.

Background: Type 2 diabetes elevates the risk of severe outcomes in COVID-19 patients, with multiple studies reporting higher case fatality rates. Metformin is a widely used medication for glycemic management. We hypothesize that improved adherence to metformin may lower COVID-19 post-infection mortality risk in this group. Utilizing data from the Mexican Social Security Institute (IMSS), we investigate the relationship between metformin adherence and mortality following COVID-19 infection in patients with chronic metformin prescriptions. Methods: This is a retrospective cohort study consisting of 61,180 IMSS beneficiaries who received a positive polymerase chain reaction (PCR) or rapid test for SARS-CoV-2 and had at least two consecutive months of metformin prescriptions prior to the positive test. The hypothetical intervention is improved adherence to metformin, measured by proportion of days covered (PDC), with the comparison being the observed metformin adherence values. The primary outcome is all-cause mortality following COVID-19 infection. We defined the causal parameter using shift intervention, an example of modified treatment policies. We used the targeted learning framework for estimation of the target estimand. Findings: Among COVID-19 positive patients with chronic metformin prescriptions, we found that a 5% and 10% absolute increase in metformin adherence is associated with a respective 0.26% (95% CI: -0.28%, 0.79%) and 1.26% (95% CI: 0.72%, 1.80%) absolute decrease in mortality risk. Interpretation: Subject to the limitations of a real-world data study, our results indicate a causal association between improved metformin adherence and reduced COVID-19 post-infection mortality risk.

Recommendations for accelerating open preprint peer review to improve the culture of science.

Peer review is an important part of the scientific process, but traditional peer review at journals is coming under increased scrutiny for its inefficiency and lack of transparency. As preprints become more widely used and accepted, they raise the possibility of rethinking the peer-review process. Preprints are enabling new forms of peer review that have the potential to be more thorough, inclusive, and collegial than traditional journal peer review, and to thus fundamentally shift the culture of peer review toward constructive collaboration. In this Consensus View, we make a call to action to stakeholders in the community to accelerate the growing momentum of preprint sharing and provide recommendations to empower researchers to provide open and constructive peer review for preprints.

How predictive of SARS-CoV-2 infection are clinical characteristics at presentation among individuals with COVID-like symptoms treated at the Mexican Institute of Social Security.

BACKGROUND: The COVID-19 pandemic has progressed rapidly, with the emergence of new virus variants that pose challenges in treating infected individuals. In Mexico, four epidemic waves have been recorded with varying disease severity. To understand the heterogeneity in clinical presentation over time and the sensitivity and specificity of signs and symptoms in identifying COVID-19 cases, an analysis of the changes in the clinical presentation of the disease was conducted. AIM: To analyze the changes in the clinical presentation of COVID-19 among 3.38 million individuals tested for SARS-CoV-2 at the Mexican Social Security Institute (IMSS) from March 2020 to October 2021 and evaluate the predictivity of signs and symptoms in identifying COVID-19 cases. METHODS: A retrospective analysis of clinical presentation patterns of COVID-19 among individuals treated at IMSS was performed, contrasting the signs and symptoms among SARS-CoV-2-positive individuals with those who tested negative for the virus but had respiratory infection symptoms. The sensitivity and specificity of each sign and symptom in identifying SARS-CoV-2 infection were estimated. RESULTS: The set of signs and symptoms reported for COVID-19-suspected patients treated at IMSS were not highly specific for SARS-CoV-2 positivity. The signs and symptoms exhibited variability based on age and epidemic wave. The area under the receiver operating characteristic (ROC) curve was 0.62 when grouping the five main symptoms (headache, dyspnea, fever, arthralgia, and cough). Most of the individual symptoms had ROC values close to 0.5 (16 out of 22 between 0.48 and 0.52), indicating non-specificity. CONCLUSIONS: The results highlight the difficulty in making a clinical diagnosis of COVID-19 due to the lack of specificity of signs and symptoms. The variability of clinical presentation over time and among age groups highlights the need for further research to differentiate whether the changes are due to changes in the virus, who is becoming infected, or the population, particularly with respect to prior infection and vaccination status.

Group psychedelic therapy: empirical estimates of cost-savings and improved access.

Objective: To compare group and individual psychedelic-assisted therapy in terms of clinician time, costs and patient access. Methods: Using 2023 data from two group therapy trial sites, one using 3,4-Methylenedioxymethamphetamine (MDMA) to treat posttraumatic stress disorder (PTSD), and one using psilocybin to treat major depressive disorder (MDD), we compared overall variable costs, clinician costs and clinician time required by therapy protocols utilizing groups versus individual patient therapy. Using published literature, we estimated the prevalence of adults with PTSD and MDD eligible for treatment with psychedelic therapy and projected the savings in time and cost required to treat these prevalent cases. Results: Group therapy saved 50.9% of clinician costs for MDMA-PTSD and 34.7% for psilocybin-MDD, or $3,467 and $981 per patient, respectively. To treat all eligible PTSD and MDD patients in the U.S. in 10 years with group therapy, 6,711 fewer full-time equivalent (FTE) clinicians for MDMA-PTSD and 1,159 fewer for FTE clinicians for psilocybin-MDD would be needed, saving up to $10.3 billion and $2.0 billion respectively, discounted at 3% annually. Conclusion: Adopting group therapy protocols where feasible would significantly reduce the cost of psychedelic-assisted therapies. By enhancing the number of patients served per clinician, group therapy could also ameliorate the anticipated shortage of appropriately trained clinicians, thereby accelerating access to these promising new therapies.

Who is most at risk of dying if infected with SARS-CoV-2? A mortality risk factor analysis using machine learning of patients with COVID-19 over time: a large population-based cohort study in Mexico.

OBJECTIVE: COVID-19 would kill fewer people if health programmes can predict who is at higher risk of mortality because resources can be targeted to protect those people from infection. We predict mortality in a very large population in Mexico with machine learning using demographic variables and pre-existing conditions. DESIGN: Cohort study. SETTING: March 2020 to November 2021 in Mexico, nationally represented. PARTICIPANTS: 1.4 million laboratory-confirmed patients with COVID-19 in Mexico at or over 20 years of age. PRIMARY AND SECONDARY OUTCOME MEASURES: Analysis is performed on data from March 2020 to November 2021 and over three phases: (1) from March to October in 2020, (2) from November 2020 to March 2021 and (3) from April to November 2021. We predict mortality using an ensemble machine learning method, super learner, and independently estimate the adjusted mortality relative risk of each pre-existing condition using targeted maximum likelihood estimation. RESULTS: Super learner fit has a high predictive performance (C-statistic: 0.907), where age is the most predictive factor for mortality. After adjusting for demographic factors, renal disease, hypertension, diabetes and obesity are the most impactful pre-existing conditions. Phase analysis shows that the adjusted mortality risk decreased over time while relative risk increased for each pre-existing condition. CONCLUSIONS: While age is the most important predictor of mortality, younger individuals with hypertension, diabetes and obesity are at comparable mortality risk as individuals who are 20 years older without any of the three conditions. Our model can be continuously updated to identify individuals who should most be protected against infection as the pandemic evolves.

Changes in the epidemiological profile of SARS-CoV-2-positive individuals in Mexico across pandemic waves as an explanation of fatality reduction: a retrospective observational study.

OBJECTIVES: We aim to quantify shifts in hospitalisation and mortality and how those were related to the first three phases of the epidemic and individuals' demographics and health profile among those with a positive test for SARS-CoV-2 treated at the Mexican Social Security Institute's facilities from March 2020 to October 2021. DESIGN: Retrospective observational study using interrupted time series analysis to identify changes in hospitalisation rate and case fatality rate (CFR) by epidemic wave. SETTING: Data from the Mexican Institute of Social Security's (IMSS) Online Influenza Epidemiological Surveillance System (SINOLAVE) that include all individuals that sought care at IMSS facilities all over Mexico. PARTICIPANTS: All individuals included in the SINOLAVE with a positive PCR or rapid test for SARS-CoV-2. PRIMARY AND SECONDARY OUTCOME MEASURES: Monthly test positivity rates, hospitalisation rates, CFRs and prevalence of relevant comorbidities by age group. RESULTS: From March 2020 to October 2021, the CFR declined between 1% and 3.5%; the declines were significant for those 0-9, 20-29, 30-39, 40-49 and 70 and older. The decline was steep during the first wave and was less steep or was temporarily reversed at the beginning of the second and third waves (changes in the trend of about 0.3% and 3.8%, and between 0.7% and 3.8%, respectively, for some age groups), but then continued to the end of the analytical period. Prevalence of diabetes, hypertension and obesity among patients testing positive also declined-two for most age groups (reductions of up to 10 percentage points for diabetes, 12 percentage points for hypertension and 19 percentage points for obesity). CONCLUSION: Data suggest that the decrease in COVID-19 fatality rate is at least partially explained by a change in the profile of those contracting the disease, that is, a falling proportion of individuals with comorbidities across all age groups.

Evolution of differences in clinical presentation across epidemic waves among patients with COVID-like-symptoms who received care at the Mexican Social Security Institute.

Background: Timely monitoring of SARS-CoV-2 variants is crucial to effectively managing both prevention and treatment efforts. In this paper, we aim to describe demographic and clinical patterns of individuals with COVID-19-like symptoms during the first three epidemic waves in Mexico to identify changes in those patterns that may reflect differences determined by virus variants. Methods: We conducted a descriptive analysis of a large database containing records for all individuals who sought care at the Mexican Social Security Institute (IMSS) due to COVID-19-like symptoms from March 2020 to October 2021 (4.48 million records). We described the clinical and demographic profile of individuals tested (3.38 million, 32% with PCR and 68% with rapid test) by test result (positives and negatives) and untested, and among those tested, and the changes in those profiles across the first three epidemic waves. Results: Individuals with COVID-19-like symptoms were older in the first wave and younger in the third one (the mean age for those positive was 46.6 in the first wave and 36.1 in the third wave; for negatives and not-tested, the mean age was 41 and 38.5 in the first wave and 34.3 and 33.5 in the third wave). As the pandemic progressed, an increasing number of individuals sought care for suspected COVID-19. The positivity rate decreased over time but remained well over the recommended 5%. The pattern of presenting symptoms changed over time, with some of those symptoms decreasing over time (dyspnea 40.6 to 14.0%, cough 80.4 to 76.2%, fever 77.5 to 65.2%, headache 80.3 to 78.5%), and some increasing (odynophagia 48.7 to 58.5%, rhinorrhea 28.6 to 47.5%, anosmia 11.8 to 23.2%, dysgeusia 11.2 to 23.2%). Conclusion: During epidemic surges, the general consensus was that any individual presenting with respiratory symptoms was a suspected COVID-19 case. However, symptoms and signs are dynamic, with clinical patterns changing not only with the evolution of the virus but also with demographic changes in the affected population. A better understanding of these changing patterns is needed to improve preparedness for future surges and pandemics.

The relationship between the gendered norm of eating last and mental health of newly married women in Nepal: A longitudinal study.

Eating last is a gendered cultural norm in which the youngest daughters-in-law are expected to eat last after serving others in the household, including men and in-laws. Using women's eating last as an indicator of women's status, we studied the association between eating last and women's mental health. Using four rounds of prospective cohort data of 18-25-year-old newly married women (n = 200) cohabiting with mothers-in-law between 2018 and 2020 in the Nawalparasi district of Nepal, we examined the association between women eating last and depressive symptom severity (measured using 15-item Hopkins Symptom Checklist for Depression; HSCL-D). Twenty-five percent of women reported eating last always. The prevalence of probable depression using the established cutoff was 5.5%, consistent with the prevalence of depression in the general population. Using a hierarchical mixed-effects linear regression model, we found that women who always ate last had an expected depressive symptom severity (0-3 on HSCL-D) 0.24 points (95% confidence interval [CI]: 0.13-0.36) greater compared to women who did not eat last when adjusted for demographic variables, household food insecurity, and secular trends. Sensitivity analysis using logistic regression also suggested that women who eat last have greater odds of having probable depression (adjusted odds ratio [AOR] = 4.05; 95% CI: 1.32-12.44). We explored if the association between eating last and depressive symptom severity was moderated by household food insecurity and did not observe evidence of moderation, underscoring the significance of eating last as a woman's status indicator. Our study findings highlight that newly young married women in Nepal are a vulnerable group.

Reaching Adolescent Girls and Young Women With HIV Self-Testing and Contraception at Girl-Friendly Drug Shops: A Randomized Trial in Tanzania.

PURPOSE: We hypothesized that an intervention designed to create girl-friendly drug shops would increase access to sexual and reproductive health products and services among adolescent girls and young women (AGYW) (ages 15-24 years) in Tanzania. METHODS: We conducted a four-month randomized trial at 20 drug shops in Shinyanga, Tanzania from August-December 2019 to determine if the Malkia Klabu ("Queen Club") intervention increased AGYW patronage and the provision of HIV self-testing (HIVST), contraception, and health facility referrals to AGYW (primary outcomes). Drug shops were randomized 1:1 to the intervention or comparison arm. All shops were provided with OraQuick HIVST kits to give to AGYW for free. Intervention shops implemented Malkia Klabu, a loyalty program for AGYW created using human-centered design through which AGYW could also access free contraception. We compared outcomes in intention-to-treat analyses using shop observations and shopkeeper records. RESULTS: By endline, shops implementing Malkia Klabu had higher AGYW patronage than comparison shops (rate ratio: 4.4; 95% confidence interval: 2.0, 9.8). Intervention shops distributed more HIVST kits (median per shop: 130.5 vs. 58.5, P = .02) and contraceptives (325.5 vs. 7.0, P < .01) to AGYW and provided more referrals for HIV, family planning, or pregnancy services combined (3.5 vs. 0.5, P = .02) than comparison shops. DISCUSSION: The Malkia Klabu intervention increased AGYW patronage and the provision of HIVST kits, contraception, and referrals to AGYW at drug shops, despite HIVST kits being freely available at all participating shops. Enhancing drug shops with girl-friendly services may be an effective strategy to reach AGYW with sexual and reproductive health services.

One vaccine to counter many diseases? Modeling the economics of oral polio vaccine against child mortality and COVID-19.

Introduction: Recent reviews summarize evidence that some vaccines have heterologous or non-specific effects (NSE), potentially offering protection against multiple pathogens. Numerous economic evaluations examine vaccines' pathogen-specific effects, but less than a handful focus on NSE. This paper addresses that gap by reporting economic evaluations of the NSE of oral polio vaccine (OPV) against under-five mortality and COVID-19. Materials and methods: We studied two settings: (1) reducing child mortality in a high-mortality setting (Guinea-Bissau) and (2) preventing COVID-19 in India. In the former, the intervention involves three annual campaigns in which children receive OPV incremental to routine immunization. In the latter, a susceptible-exposed-infectious-recovered model was developed to estimate the population benefits of two scenarios, in which OPV would be co-administered alongside COVID-19 vaccines. Incremental cost-effectiveness and benefit-cost ratios were modeled for ranges of intervention effectiveness estimates to supplement the headline numbers and account for heterogeneity and uncertainty. Results: For child mortality, headline cost-effectiveness was $650 per child death averted. For COVID-19, assuming OPV had 20% effectiveness, incremental cost per death averted was $23,000-65,000 if it were administered simultaneously with a COVID-19 vaccine <200 days into a wave of the epidemic. If the COVID-19 vaccine availability were delayed, the cost per averted death would decrease to $2600-6100. Estimated benefit-to-cost ratios vary but are consistently high. Discussion: Economic evaluation suggests the potential of OPV to efficiently reduce child mortality in high mortality environments. Likewise, within a broad range of assumed effect sizes, OPV (or another vaccine with NSE) could play an economically attractive role against COVID-19 in countries facing COVID-19 vaccine delays. Funding: The contribution by DTJ was supported through grants from Trond Mohn Foundation (BFS2019MT02) and Norad (RAF-18/0009) through the Bergen Center for Ethics and Priority Setting.

The Impact Of COVID-19 On The Health Of Incarcerated Older Adults In California State Prisons.

The number of older adults (age fifty-five or older) incarcerated in US prisons reached an all-time high just as COVID-19 entered correctional facilities in 2020. However, little is known about COVID-19's impact on incarcerated older adults. We compared COVID-19 outcomes between older and younger adults in California state prisons from March 1, 2020, to October 9, 2021. Adjusted odds ratios (aORs) revealed an increasing risk for adverse COVID-19 outcomes among older age groups (ages 55-64, 65-74, and 75 or older) compared with younger adults, including for documented infection (aOR, 1.3, 1.4, and 1.4, respectively) and hospitalization with COVID-19 (aOR, 4.6, 8.7, and 15.1, respectively). Moreover, although accounting for 17.3 percent of the California state prison population, older adults represented 85.8 percent of this population's COVID-19-related deaths. Yet a smaller percentage of older adults than younger adults were released from prison during the pandemic. The differential rates of morbidity and mortality experienced by incarcerated older adults should be considered in future pandemic response strategies regarding prisons.

Modeling scenarios for mitigating outbreaks in congregate settings.

The explosive outbreaks of COVID-19 seen in congregate settings such as prisons and nursing homes, has highlighted a critical need for effective outbreak prevention and mitigation strategies for these settings. Here we consider how different types of control interventions impact the expected number of symptomatic infections due to outbreaks. Introduction of disease into the resident population from the community is modeled as a stochastic point process coupled to a branching process, while spread between residents is modeled via a deterministic compartmental model that accounts for depletion of susceptible individuals. Control is modeled as a proportional decrease in the number of susceptible residents, the reproduction number, and/or the proportion of symptomatic infections. This permits a range of assumptions about the density dependence of transmission and modes of protection by vaccination, depopulation and other types of control. We find that vaccination or depopulation can have a greater than linear effect on the expected number of cases. For example, assuming a reproduction number of 3.0 with density-dependent transmission, we find that preemptively reducing the size of the susceptible population by 20% reduced overall disease burden by 47%. In some circumstances, it may be possible to reduce the risk and burden of disease outbreaks by optimizing the way a group of residents are apportioned into distinct residential units. The optimal apportionment may be different depending on whether the goal is to reduce the probability of an outbreak occurring, or the expected number of cases from outbreak dynamics. In other circumstances there may be an opportunity to implement reactive disease control measures in which the number of susceptible individuals is rapidly reduced once an outbreak has been detected to occur. Reactive control is most effective when the reproduction number is not too high, and there is minimal delay in implementing control. We highlight the California state prison system as an example for how these findings provide a quantitative framework for understanding disease transmission in congregate settings. Our approach and accompanying interactive website (https://phoebelu.shinyapps.io/DepopulationModels/) provides a quantitative framework to evaluate the potential impact of policy decisions governing infection control in outbreak settings.

Respiratory pandemic preparedness learnings from the June 2020 COVID-19 outbreak at San Quentin California State Prison.

PURPOSE: This study aims to characterize the June 2020 COVID-19 outbreak at San Quentin California State Prison and to describe what made San Quentin so vulnerable to uncontrolled transmission. DESIGN/METHODOLOGY/APPROACH: Since its onset, the COVID-19 pandemic has exposed and exacerbated the profound health harms of carceral settings, such that nearly half of state prisons reported COVID-19 infection rates that were four or more times (and up to 15 times) the rate found in the state's general population. Thus, addressing the public health crises and inequities of carceral settings during a respiratory pandemic requires analyzing the myriad factors shaping them. In this study, we reported observations and findings from environmental risk assessments during visits to San Quentin California State Prison. We complemented our assessments with analyses of administrative data. FINDINGS: For future respiratory pathogens that cannot be prevented with effective vaccines, this study argues that outbreaks will no doubt occur again without robust implementation of additional levels of preparedness - improved ventilation, air filtration, decarceration with emergency evacuation planning - alongside addressing the vulnerabilities of carceral settings themselves. ORIGINALITY/VALUE: This study addresses two critical aspects that are insufficiently covered in the literature: how to prepare processes to safely implement emergency epidemic measures when needed, such as potential evacuation, and how to address unique challenges throughout an evolving pandemic for each carceral setting.

COVID-19 outbreak in a state prison: a case study on the implementation of key public health recommendations for containment and prevention.

BACKGROUND: People incarcerated in US prisons have been disproportionately harmed by the COVID-19 pandemic. That prisons are such efficient superspreading environments can be attributed to several known factors: small, communal facilities where people are confined for prolonged periods of time; poor ventilation; a lack of non-punitive areas for quarantine/medical isolation; and staggeringly high numbers of people experiencing incarceration, among others. While health organizations have issued guidance on preventing and mitigating COVID-19 infection in carceral settings, little is known about if, when, and how recommendations have been implemented. We examined factors contributing to containment of one of the first California prison COVID-19 outbreaks and remaining vulnerabilities using an adapted multi-level determinants framework to systematically assess infectious disease risk in carceral settings. METHODS: Case study employing administrative data; observation; and informal discussions with: people incarcerated at the prison, staff, and county public health officials. RESULTS: Outbreak mitigation efforts were characterized by pre-planning (e.g., designation of ventilated, single-occupancy quarantine) and a quickly mobilized inter-institutional response that facilitated systematic, voluntary rapid testing. However, several systemic- and institutional-level vulnerabilities were unaddressed hindering efforts and posing significant risk for future outbreaks, including insufficient decarceration, continued inter-facility transfers, incomplete staff cohorting, and incompatibility between built environment features (e.g., dense living conditions) and public health recommendations. CONCLUSIONS: Our adapted framework facilitates systematically assessing prison-based infectious disease outbreaks and multi-level interventions. We find implementing some recommended public health strategies may have contributed to outbreak containment. However, even with a rapidly mobilized, inter-institutional response, failure to decarcerate created an overreliance on chance conditions. This left the facility vulnerable to future catastrophic outbreaks and may render standard public health strategies - including the introduction of effective vaccines - insufficient to prevent or contain those outbreaks.

Scaling up public mental health care in Sub-Saharan Africa: insights from infectious disease.

INTRODUCTION: Models estimate that the disability burden from mental disorders in Sub-Saharan Africa (SSA) will more than double in the next 40 years. Similar to HIV, mental disorders are stigmatized in many SSA settings and addressing them requires community engagement and long-term treatment. Yet, in contrast to HIV, the public mental healthcare cascade has not been sustained, despite robust data on scalable strategies. We draw on findings from our International AIDS Society (IAS) 2020 virtual workshop and make recommendations for next steps in the scale up of the SSA public mental healthcare continuum. DISCUSSION: Early HIV surveillance and care cascade targets are discussed as important strategies for HIV response in SSA that should be adopted for mental health. Advocacy, including engagement with civil society, and targeted economic arguments to policymakers, are reviewed in the context of HIV success in SSA. Parallel opportunities for mental disorders are identified. Learning from HIV, communication of strategies that advance mental health care needs in SSA must be prioritized for broad global audiences. CONCLUSIONS: The COVID-19 pandemic is setting off a colossal escalation of global mental health care needs, well-publicized across scientific, media, policymaker, and civil society domains. The pandemic highlights disparities in healthcare access and reinvigorates the push for universal coverage. Learning from HIV strategies, we must seize this historical moment to improve the public mental health care cascade in SSA and capitalize on the powerful alliances ready to be forged. As noted by Ambassador Goosby in our AIDS 2020 workshop, 'The time is now'.

Mitigating outbreaks in congregate settings by decreasing the size of the susceptible population.

While many transmission models have been developed for community spread of respiratory pathogens, less attention has been given to modeling the interdependence of disease introduction and spread seen in congregate settings, such as prisons or nursing homes. As demonstrated by the explosive outbreaks of COVID-19 seen in congregate settings, the need for effective outbreak prevention and mitigation strategies for these settings is critical. Here we consider how interventions that decrease the size of the susceptible populations, such as vaccination or depopulation, impact the expected number of infections due to outbreaks. Introduction of disease into the resident population from the community is modeled as a branching process, while spread between residents is modeled via a compartmental model. Control is modeled as a proportional decrease in both the number of susceptible residents and the reproduction number. We find that vaccination or depopulation can have a greater than linear effect on anticipated infections. For example, assuming a reproduction number of 3.0 for density-dependent COVID-19 transmission, we find that reducing the size of the susceptible population by 20% reduced overall disease burden by 47%. We highlight the California state prison system as an example for how these findings provide a quantitative framework for implementing infection control in congregate settings. Additional applications of our modeling framework include optimizing the distribution of residents into independent residential units, and comparison of preemptive versus reactive vaccination strategies.

Old vaccines for new infections: Exploiting innate immunity to control COVID-19 and prevent future pandemics.

The COVID-19 pandemic triggered an unparalleled pursuit of vaccines to induce specific adaptive immunity, based on virus-neutralizing antibodies and T cell responses. Although several vaccines have been developed just a year after SARS-CoV-2 emerged in late 2019, global deployment will take months or even years. Meanwhile, the virus continues to take a severe toll on human life and exact substantial economic costs. Innate immunity is fundamental to mammalian host defense capacity to combat infections. Innate immune responses, triggered by a family of pattern recognition receptors, induce interferons and other cytokines and activate both myeloid and lymphoid immune cells to provide protection against a wide range of pathogens. Epidemiological and biological evidence suggests that the live-attenuated vaccines (LAV) targeting tuberculosis, measles, and polio induce protective innate immunity by a newly described form of immunological memory termed "trained immunity." An LAV designed to induce adaptive immunity targeting a particular pathogen may also induce innate immunity that mitigates other infectious diseases, including COVID-19, as well as future pandemic threats. Deployment of existing LAVs early in pandemics could complement the development of specific vaccines, bridging the protection gap until specific vaccines arrive. The broad protection induced by LAVs would not be compromised by potential antigenic drift (immune escape) that can render viruses resistant to specific vaccines. LAVs might offer an essential tool to "bend the pandemic curve," averting the exhaustion of public health resources and preventing needless deaths and may also have therapeutic benefits if used for postexposure prophylaxis of disease.

Non-communicable diseases and inequalities increase risk of death among COVID-19 patients in Mexico.

BACKGROUND: The SARS-CoV-2 pandemic compounds Mexico's pre-existing challenges: very high levels of both non-communicable diseases (NCD) and social inequity. METHODS AND FINDINGS: Using data from national reporting of SARS-CoV-2 tested individuals, we estimated odds of hospitalization, intubation, and death based on pre-existing non-communicable diseases and socioeconomic indicators. We found that obesity, diabetes, and hypertension are positively associated with the three outcomes in a synergistic manner. The municipal poverty level is also positively associated with hospitalization and death. CONCLUSIONS: Mexico's response to COVID-19 is complicated by a synergistic double challenge: raging NCDs and extreme social inequity. The response to the current pandemic must take both into account both to be effective and to ensure that the burden of COVID-19 not falls disproportionately on those who are already disadvantaged.