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.

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'.

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.