Recent and forecasted increases in coccidioidomycosis incidence in California linked to hydroclimatic swings.

Coccidioidomycosis, or Valley fever, is an infectious disease caused by inhalation of Coccidioides spp., fungi found primarily in soils of the southwestern United States. Prior work showed that coccidioidomycosis cases in California sharply increase by nearly 2-fold following wet winters that occur one- and two-years following drought. Statewide drought between 2020-2022 followed by heavy precipitation during the 2022-2023 winter raised concerns over potential increases in coccidioidomycosis cases in the fall of 2023, prompting California Department of Public Health (CDPH) to issue public health alerts. As anticipated, California saw a near record number of cases in 2023, with 9,054 provisional cases reported. During the 2023-2024 California wet season, precipitation was 115% the long-term average, furthering concerns about continued high coccidioidomycosis risk. We developed an ensemble model to forecast coccidioidomycosis cases in California in 2024-2025. Using this model, we predicted a total of 11,846 cases (90% PI: 10,056-14,094) in California between April 1, 2023, and March 31, 2024, encompassing the preliminary state report of 10,593. Our model forecasted 12,244 cases statewide between April 1, 2024, and March 31, 2025 - a 62% increase over the cases reported during the same period two years prior, and on par with the high incidence seen in 2023. The Southern San Joaquin Valley (5,398 cases, 90% PI: 4,556-6,442), Southern Coast (3,322, 90% PI: 2,694-3,961), and Central Coast (1,207 cases, 90% PI: 867-1,585) regions are expected to see the largest number of infections. Our model forecasts that disease incidence will exhibit pronounced seasonality, particularly in endemic regions, with cases rising in June and peaking in November at 1,411 (90% PI: 815-2,172) cases statewide - 98% higher than the peak two years prior (714) and nearly as high as the peak in 2023 (1,462). Near-term forecasts have the potential to inform public health messaging to enhance provider and patient awareness, encourage risk reduction practices, and improve recognition and management of coccidioidomycosis.

Coccidioidomycosis seasonality in California: a longitudinal surveillance study of the climate determinants and spatiotemporal variability of seasonal dynamics, 2000-2021.

Background: Coccidioidomycosis, an emerging fungal disease in the western USA, exhibits seasonal patterns that are poorly understood, including periods of strong cyclicity, aseasonal intervals, and variation in seasonal timing that have been minimally characterized, and unexplained as to their causal factors. Coccidioidomycosis incidence has increased markedly in recent years, and our limited understanding of intra- and inter-annual seasonality has hindered the identification of important drivers of disease transmission, including climate conditions. In this study, we aim to characterize coccidioidomycosis seasonality in endemic regions of California and to estimate the relationship between drought conditions and coccidioidomycosis seasonal periodicity and timing. Methods: We analysed data on all reported incident cases of coccidioidomycosis in California from 2000 to 2021 to characterize seasonal patterns in incidence, and conducted wavelet analyses to assess the dominant periodicity, power, and timing of incidence for 17 counties with consistently high incidence rates. We assessed associations between seasonality parameters and measures of drought in California using a distributed lag nonlinear modelling framework. Findings: All counties exhibited annual cyclicity in incidence (i.e., a dominant wavelet periodicity of 12 months), but there was considerable heterogeneity in seasonal strength and timing across regions and years. On average, 12-month periodicity was most pronounced in the Southern San Joaquin Valley and Central Coast. Further, the annual seasonal cycles in the Southern San Joaquin Valley and the Southern Inland regions occurred earlier than those in coastal and northern counties, yet the timing of annual cycles became more aligned among counties by the end of the study period. Drought conditions were associated with a strong attenuation of the annual seasonal cycle, and seasonal peaks became more pronounced in the 1-2 years after a drought ended. Interpretation: We conclude that drought conditions do not increase the risk of coccidioidomycosis onset uniformly across the year, but instead promote increased risk concentrated within a specific calendar period (September to December). The findings have important implications for public health preparedness, and for how future shifts in seasonal climate patterns and extreme events may impact spatial and temporal coccidioidomycosis risk. Funding: National Institutes of Health.

Satisfaction of mothers with supplementary nutritional services through Anganwadi centres in an urban area of Meerut, India.

Background: Undernutrition in children under 5 years of age is still a great public health burden. Integrated child development services (ICDS) were launched with an idea of making a dent on this age-old issue. Various studies in the past have been done to identify lacunae in the programme, but very few studies are done focussing on the satisfaction of mothers with the supplementary nutrition provided through ICDS programme. The utilisation of the programme depends on various factors, one of which is client satisfaction. Methods and Material: The Anganwadi centres of urban areas of Meerut were line-listed after taking a list of Anganwadis from the Child Development Office. There are 297 Anganwadis in urban areas of Meerut. With help of random number tables, three Anganwadis were selected, and to complete the sample of 152, 51 children from two Anganwadis and 50 from one Anganwadi centre were selected with help of simple random tables. The data thus collected were analysed using Epiinfo version 7.2.3.1. Results: The prevalence of underweight was found to be 34.2%, wasted 19.7%, and stunted 11.2%. Among the characteristics assessed, a majority of mothers, 58.5%, were dissatisfied with the frequency at which supplementary nutrition was provided from the Anganwadis. All children were provided Take Home Ration, and 100.0% of mothers reported using it for all family members. Still 63.2% of mothers were unaware about the iron supplementation in childhood and only 65.8% of mothers had satisfactory handwashing practices. Conclusions: In this study, a majority of mothers were dissatisfied with the frequency at which supplementary nutrition was provided to their children. Also, the prevalence of underweight children was significantly higher when mothers were not aware about the factors affecting nutrition in children. The Take Home Ration given for children was shared among family members in 100.0% families.

Defining long COVID using a population-based SARS-CoV-2 survey in California.

BACKGROUND: More than four years after the start of the COVID-19 pandemic, understanding of SARS-CoV-2 burden and post-acute sequela of COVID (PASC), or long COVID, continues to evolve. However, prevalence estimates are disparate and uncertain. Leveraging survey responses from a large serosurveillance study, we assess prevalence estimates using five different long COVID definitions among California residents. METHODS: The California Department of Public Health (CDPH) conducted a cross-sectional survey that included questions about acute COVID-19 infection and recovery. A random selection of California households was invited to participate in a survey that included demographic information, clinical symptoms, and COVID-19 vaccination history. We assessed prevalence and predictors of long COVID among those previously testing positive for SARS-CoV-2 across different definitions using logistic regression. FINDINGS: A total of 2883 participants were included in this analysis; the majority identified as female (62.5 %), and the median age was 39 years (interquartile range: 17-55 years). We found a significant difference in long COVID prevalence across definitions with the highest prevalence observed when participants were asked about incomplete recovery (20.9 %, 95 % confidence interval [CI]: 19.4-22.5) and the lowest prevalence was associated with severe long COVID affecting an estimated 4.9 % (95 % CI 4.1-5.7) of the participant population. Individuals that completed the primary vaccination series had significantly lower prevalence of long COVID compared to those that did not receive COVID vaccination. INTERPRETATION: There were significant differences in the estimated prevalence of long COVID across different definitions. People who experience a severe initial COVID-19 infection should be considered at a higher probability for developing long COVID. FUNDING: Centers for Disease Control and Prevention - Epidemiology and Laboratory Capacity.

Prevalence of hypertension, screening, awareness, and associated risk factors in teaching institution of Etawah District, Uttar Pradesh: A cross-section study.

Background: Hypertension is one of the leading causes of death worldwide, affecting over one billion people. It is responsible for roughly half of all heart disease and stroke-related deaths globally. Because hypertension does not cause any symptoms on its own, it is commonly referred to as "the silent killer." Objective: This study aimed to determine (1) the prevalence of hypertension and its associated risk factors and (2) the level of awareness of hypertension status among study participants. Material and Methods: A facility-based cross-sectional analytical study was conducted for 3 months during January-March 2023 at the teaching institution in Etawah District, Uttar Pradesh. It was conducted among 392 study participants who were ≥18 years old. Data were collected through a predesigned, pretested, semi-structured questionnaire, and anthropometric measurement was determined using standard guidelines. Results: The overall prevalence of hypertension screening was 69.4% (male: 33.8% and female: 66.2%), respectively. The majority of hypertensives were found in female participants. Tobacco and alcohol consumption, obesity, physical inactivity, stress and strain, and an unhealthy diet were also associated with hypertension. Among 392 study participants, only 67 (24.6%) were aware of their hypertension status. Conclusion: We conclude that hypertension has been described as an "Iceberg disease" as those who suffer are usually unaware and hence usually seek healthcare services at a very late stage. Preventive measures should be needed to improve hypertension screening, awareness, treatment, and control.

Demographic changes in COVID-19 mortality during the pandemic: analysis of trends in disparities among workers using California's mortality surveillance system.

BACKGROUND: There is limited information on the extent and patterns of disparities in COVID-19 mortality throughout the pandemic. We aimed to examine trends in disparities by demographics over variants in the pre- and post-vaccine availability period among Californian workers using a social determinants of health lens. METHODS: Using death certificates, we identified all COVID-19 deaths that occurred between January 2020 and May 2022 among workers aged 18-64 years in California (CA). We derived estimates for at-risk worker populations using the Current Population Survey. The waves of COVID-19 mortality in the pre-vaccine availability period were March 2020-June 2020 (wave 1), and July 2020-November 2020 (wave 2), and in the post-vaccine availability period: December 2020-May 2021 (wave 3), June 2021-January 2022 (wave 4), and February 2022-May 2022 (wave 5). Poisson regression models with robust standard errors were used to determine wave-specific mortality rate ratios (MRRs). We examined the change in MRR across waves by including an interaction term between each demographic characteristic and wave period in different models. The role of potential misclassification of Race/ethnicity on death certificates was examined using probabilistic quantitative bias analysis as sensitivity analysis. RESULTS: Among the 24.1 million working age CA population included in the study, there were 26,068 COVID-19 deaths in the period between January 2020 and May 2022. Compared with their respective reference groups, workers who were 50-64 years old, male, Native Hawaiian, Latino, or African American, foreign-born; individuals who had lower education; and unmarried were disproportionately affected by COVID-19 mortality. While disparities by sex, race/ethnicity and foreign-born status narrowed in later waves (post-vaccine availability), disparities by age, education level and marital status did not change substantially across waves. CONCLUSION: Demographic disparities in COVID-19 mortality narrowed in the post-vaccine availability waves. However, the existence of disparities across all waves of the pandemic, even in an era of widespread vaccine coverage, could indicate remaining gaps in prevention and differential vulnerability. Addressing the underlying social, structural, and occupational factors that contribute to these disparities is critical for achieving health equity.

Impact of Lifestyle Modification: An Intervention on Newly Diagnosed Diabetics of the Urban Slum of Meerut.

Introduction Diabetes is a long-term condition that necessitates ongoing medical attention and self-care to prevent immediate complications and minimize the likelihood of long-term issues. Early diagnosis is one of the most important steps for people living with diabetes to take. Public awareness regarding the importance of lifestyle modification in managing type 2 diabetes mellitus is a crucial preventive measure. Despite continuous efforts to raise public awareness, the prevalence of type 2 diabetes continues to increase, with most people overlooking the importance of a healthy lifestyle. Our goal was to assess the impact of lifestyle modification on glycemic control in newly diagnosed diabetic patients. Materials and methods A total of 503 adults aged 30 years and above who were nondiabetic or were unaware of their diabetic status were assessed for their fasting blood glucose levels. Individuals identified as diabetic based on their fasting blood glucose levels were subjected to lifestyle modification for a period of three months. Glycemic levels were measured at the beginning and the end of the study period for comparison. Results Of the study participants, 7.6% were undiagnosed diabetics with increased blood sugar levels who were unaware of their diabetic status. Mean anthropometric measurements from pre- to postintervention values improved overall. Overall reduction was observed in weight (66.21±12.97 to 63.18±11.48), waist circumference (96.21±13.01 to 91.77±11.82), hip circumference (105.16±11.91 to 103.58±10.88), waist-hip ratio (0.91±0.09 to 0.88±0.08) and body mass index (27.48±6.04 to 26.18±5.30). Significant reductions were observed in the mean glycemic values, including fasting blood sugar (180.19±55.81 to 152.56±45.74) and glycosylated hemoglobin levels (8.61±1.97 to 6.68±1.67). Conclusion Lifestyle modification plays a crucial role in managing diabetes, both in preventing its onset and controlling its progression. The present study highlights the importance of early diagnosis and lifestyle interventions in the management of diabetes, thereby stressing the necessity of comprehensive strategies to combat this situation.

Mixed methods approach to examining the implementation experience of a phone-based survey for a SARS-CoV-2 test-negative case-control study in California.

OBJECTIVE: To describe the implementation of a test-negative design case-control study in California during the Coronavirus Disease 2019 (COVID-19) pandemic. STUDY DESIGN: Test-negative case-control study. METHODS: Between February 24, 2021 - February 24, 2022, a team of 34 interviewers called 38,470 Californians, enrolling 1,885 that tested positive for SARS-CoV-2 (cases) and 1,871 testing negative for SARS-CoV-2 (controls) for 20-minute telephone survey. We estimated adjusted odds ratios for answering the phone and consenting to participate using mixed effects logistic regression. We used a web-based anonymous survey to compile interviewer experiences. RESULTS: Cases had 1.29-fold (95% CI: 1.24-1.35) higher adjusted odds of answering the phone and 1.69-fold (1.56-1.83) higher adjusted odds of consenting to participate compared to controls. Calls placed from 4pm to 6pm had the highest adjusted odds of being answered. Some interviewers experienced mental wellness challenges interacting with participants with physical (e.g., food, shelter, etc.) and emotional (e.g., grief counseling) needs, and enduring verbal harassment from individuals called. CONCLUSIONS: Calls placed during afternoon hours may optimize response rate when enrolling controls to a case-control study during a public health emergency response. Proactive check-ins and continual collection of interviewer experience(s) and may help maintain mental wellbeing of investigation workforce. Remaining adaptive to the dynamic needs of the investigation team is critical to a successful study, especially in emergent public health crises, like that represented by the COVID-19 pandemic.

CalScope: methodology and lessons learned for conducting a remote statewide SARS-CoV-2 seroprevalence study in California using an at-home dried blood spot collection kit and online survey.

BACKGROUND: To describe the methodology for conducting the CalScope study, a remote, population-based survey launched by the California Department of Public Health (CDPH) to estimate SARS-CoV-2 seroprevalence and understand COVID-19 disease burden in California. METHODS: Between April 2021 and August 2022, 666,857 randomly selected households were invited by mail to complete an online survey and at-home test kit for up to one adult and one child. A gift card was given for each completed survey and test kit. Multiple customized REDCap databases were used to create a data system which provided task automation and scalable data management through API integrations. Support infrastructure was developed to manage follow-up for participant questions and a communications plan was used for outreach through local partners. RESULTS: Across 3 waves, 32,671 out of 666,857 (4.9%) households registered, 6.3% by phone using an interactive voice response (IVR) system and 95.7% in English. Overall, 25,488 (78.0%) households completed surveys, while 23,396 (71.6%) households returned blood samples for testing. Support requests (n = 5,807) received through the web-based form (36.3%), by email (34.1%), and voicemail (29.7%) were mostly concerned with the test kit (31.6%), test result (26.8%), and gift card (21.3%). CONCLUSIONS: Ensuring a well-integrated and scalable data system, responsive support infrastructure for participant follow-up, and appropriate academic and local health department partnerships for study management and communication allowed for successful rollout of a large population-based survey. Remote data collection utilizing online surveys and at-home test kits can complement routine surveillance data for a state health department.

California's COVID-19 Vaccine Equity Policy: Cases, Hospitalizations, And Deaths Averted In Affected Communities.

In March 2021, California implemented a vaccine equity policy that prioritized COVID-19 vaccine allocation to communities identified as least advantaged by an area-based socioeconomic measure, the Healthy Places Index. We conducted quasi-experimental and counterfactual analyses to estimate the effect of this policy on COVID-19 vaccination, case, hospitalization, and death rates. Among prioritized communities, vaccination rates increased 28.4 percent after policy implementation. Furthermore, an estimated 160,892 COVID-19 cases, 10,248 hospitalizations, and 679 deaths in the least-advantaged communities were averted by the policy. Despite these improvements, the share of COVID-19 cases, hospitalizations, and deaths in prioritized communities remained elevated. These estimates were robust in sensitivity analyses that tested exchangeability between prioritized communities and those not prioritized by the policy; model specifications; and potential temporal confounders, including prior infections. Correcting for disparities by strategically allocating limited resources to the least-advantaged or most-affected communities can reduce the impacts of COVID-19 and other diseases but might not eliminate health disparities.

Interim Influenza Vaccine Effectiveness Against Laboratory-Confirmed Influenza - California, October 2023-January 2024.

Surveillance data can provide rapid, within-season influenza vaccine effectiveness (VE) estimates to guide public health recommendations. Mandatory reporting of influenza vaccine administration to California's immunization information registry began January 1, 2023, and mandatory reporting of all influenza laboratory test results, including negative results, was instituted in California on June 15, 2023. These data, collected by the California Department of Public Health during October 1, 2023-January 31, 2024, were used to calculate interim influenza VE against laboratory-confirmed influenza by comparing the odds of vaccination among case-patients (persons who received a positive influenza laboratory test result) and control patients (those who received a negative influenza laboratory test result). VE was calculated as 1 - adjusted odds ratio using mixed-effects logistic regression, with age, race, and ethnicity as fixed effects and specimen collection week and county as random effects. Overall, during October 1, 2023-January 31, 2024, estimated VE was 45% among persons aged ≥6 months, 56% among children and adolescents aged 6 months-17 years, 48% among adults aged 18-49 years, 36% among those aged 50-64 years, and 30% among those aged ≥65 years. Consistent with some previous influenza seasons, influenza vaccination provided moderate protection against laboratory-confirmed influenza among infants, children, adolescents, and adults. All persons aged ≥6 months without a contraindication to vaccination should receive annual influenza vaccination to reduce influenza illness, severe influenza, and strain on health care resources. Influenza vaccination remains the best way to prevent influenza.

The Intersection of Childcare and Health Among Women at a U.S. Safety-Net Health System During the COVID-19 Pandemic: A Qualitative Study.

Introduction: Lack of childcare has been linked to missed health care appointments for adult women, especially for lower-income women. The COVID-19 pandemic created additional stressors for many low-income families that already struggled to meet childcare and health care needs. By exploring the experiences of women who were referred for childcare services at a U.S. safety-net health system, we aimed to understand the challenges women faced in managing their health and childcare needs during the COVID-19 pandemic. Methods: We conducted semistructured interviews with participants in Dallas County, TX between August 2021 and February 2022. All participants were referred from women's health clinics at the county's safety-net hospital system to an on-site drop-off childcare center by hospital staff who identified lack of childcare as a barrier to health care access. Participants were the primary caregiver for at least one child ≤age 13. Interviews were conducted in English or Spanish. We analyzed data using thematic content analysis. Results: We interviewed 22 participants (mean age 34); participants were adult women, had on average 3 children, and primarily identified as Hispanic or African American. Three interrelated themes emerged: disruptions in access, competing priorities, and exacerbated psychological distress. Conclusions: Findings demonstrate how low-income women with young children in a safety-net health system struggle to address their own health needs amid childcare and other household demands. Our study advances our understanding of childcare as a social domain of health, a necessary step to inform how we build structural support systems and drive policy interventions.

Tuberculosis Diagnostic Delays and Treatment Outcomes among Patients with COVID-19, California, USA, 2020.

We assessed tuberculosis (TB) diagnostic delays among patients with TB and COVID-19 in California, USA. Among 58 persons, 43% experienced TB diagnostic delays, and a high proportion (83%) required hospitalization for TB. Even when viral respiratory pathogens circulate widely, timely TB diagnostic workup for at-risk persons remains critical for reducing TB-related illness.

Longitudinal efficacy of Ertugliflozin in type 2 diabetes mellitus: a meta-analysis of randomized controlled trials.

INTRODUCTION: Ertugliflozin, a sodium-glucose cotransporter-2 inhibitor, seems to improve glycemic control in type 2 diabetes mellitus (T2DM). We aim to evaluate the efficacy of Ertugliflozin across multiple time intervals (18, 26, and 52 weeks) in T2DM patients. METHODS: A literature search was conducted on electronic databases. Data was extracted from eligible studies at both 5 mg and 15 mg doses in monotherapy and as add-on therapy. Cochrane RevMan was used to perform the meta-analysis. RESULTS: Ertugliflozin, at both 5 mg and 15 mg doses, demonstrated a significant improvement in HbA1c levels at 18 weeks 5 mg [P = 0.00001], 15 mg [P = 0.05], and at 26 weeks in monotherapy 5 mg [P = 0.006], monotherapy 15 mg [P = 0.006], 5 mg as add-on therapy [P = 0.00001], 15 mg add-on therapy [P = 0.00001] respectively. At 52 weeks, the reduction in HbA1c was significant in 15 mg add-on therapy [P = 0.0001]. Additionally, ertugliflozin as an add-on therapy also led to a significant reduction in FPG, body weight, and systolic blood pressure. CONCLUSION: Ertugliflozin showed clinical efficacy in improving glycemic control, fasting plasma glucose, body weight, and systolic blood pressure in T2DM patients over the studied time intervals compared to placebo.

Predicting the Public Health Impact of Bivalent Vaccines and Nirmatrelvir-Ritonavir Against Coronavirus Disease 2019.

Background: Uptake of coronavirus disease 2019 (COVID-19) bivalent vaccines and the oral medication nirmatrelvir-ritonavir (Paxlovid) has remained low across the United States. Assessing the public health impact of increasing uptake of these interventions in key risk groups can guide further public health resources and policy and determine what proportion of severe COVID-19 is avertable with these interventions. Methods: This modeling study used person-level data from the California Department of Public Health on COVID-19 cases, hospitalizations, deaths, and vaccine administration from 23 July 2022 to 23 January 2023. We used a quasi-Poisson regression model calibrated to recent historical data to predict future COVID-19 outcomes and modeled the impact of increasing uptake (up to 70% coverage) of bivalent COVID-19 vaccines and nirmatrelvir-ritonavir during acute illness in different risk groups. Risk groups were defined by age (≥50, ≥65, ≥75 years) and vaccination status (everyone, primary series only, previously vaccinated). We predicted the number of averted COVID-19 cases, hospitalizations, and deaths and number needed to treat (NNT). Results: The model predicted that increased uptake of bivalent COVID-19 boosters and nirmatrelvir-ritonavir (up to 70% coverage) in all eligible persons could avert an estimated 15.7% (95% uncertainty interval [UI], 11.2%-20.7%; NNT: 17 310) and 23.5% (95% UI, 13.1%-30.0%; NNT: 67) of total COVID-19-related deaths, respectively. In the high-risk group of persons ≥65 years old alone, increased uptake of bivalent boosters and nirmatrelvir-ritonavir could avert an estimated 11.9% (95% UI, 8.4%-15.1%; NNT: 2757) and 22.8% (95% UI, 12.7%-29.2%; NNT: 50) of total COVID-19-related deaths, respectively. Conclusions: These findings suggest that prioritizing uptake of bivalent boosters and nirmatrelvir-ritonavir among older age groups (≥65 years) would be most effective (based on NNT) but would not address the entire burden of severe COVID-19.

Temporal assessment of disparities in California COVID-19 mortality by industry: a population-based retrospective cohort study.

PURPOSE: To assess changes in the COVID-19 mortality rate and disparities over variants or waves by industry. METHODS: We identified COVID-19 deaths that occurred between January 2020 and May 2022 among California workers aged 18-64 years using death certificates, and estimated Californians at risk using the Current Population Survey. The waves in deaths were wave 1: March-June 2020, wave 2: July-November 2020, wave 3/Epsilon and Alpha variants: December 2020-May 2021, wave 4/Delta variant: June 2021-January 2022, and wave 5/Omicron variant: February-May 2022. We used Poisson regression to generate wave-specific mortality rate ratios (MRR) and included an interaction term between industry and wave in different models to assess significance of the change in MRR. RESULTS: In all waves of the pandemic, healthcare, other services, manufacturing, transportation, and retail trade industries had higher mortality rates than the professional, scientific, and technical industry. The healthcare industry had the highest relative rate earlier in the pandemic, while other services, utilities, and accommodation and food services industries had substantial increases in MRR in later waves. CONCLUSIONS: Industries that consistently had disproportionate COVID-19 mortality may have benefitted from protections that consider workers' increased exposure and vulnerability to severe outcomes.

Correlation between wastewater and COVID-19 case incidence rates in major California sewersheds across three variant periods.

Monitoring for COVID-19 through wastewater has been used for adjunctive public health surveillance, with SARS-CoV-2 viral concentrations in wastewater correlating with incident cases in the same sewershed. However, the generalizability of these findings across sewersheds, laboratory methods, and time periods with changing variants and underlying population immunity has not been well described. The California Department of Public Health partnered with six wastewater treatment plants starting in January 2021 to monitor wastewater for SARS-CoV-2, with analyses performed at four laboratories. Using reported PCR-confirmed COVID-19 cases within each sewershed, the relationship between case incidence rates and wastewater concentrations collected over 14 months was evaluated using Spearman's correlation and linear regression. Strong correlations were observed when wastewater concentrations and incidence rates were averaged (10- and 7-day moving window for wastewater and cases, respectively, ρ = 0.73-0.98 for N1 gene target). Correlations remained strong across three time periods with distinct circulating variants and vaccination rates (winter 2020-2021/Alpha, summer 2021/Delta, and winter 2021-2022/Omicron). Linear regression revealed that slopes of associations varied by the dominant variant of concern, sewershed, and laboratory (ß = 0.45-1.94). These findings support wastewater surveillance as an adjunctive public health tool to monitor SARS-CoV-2 community trends.

Association between wildfires and coccidioidomycosis incidence in California, 2000-2018: a synthetic control analysis.

The frequency and severity of wildfires in the Western United States have increased over recent decades, motivating hypotheses that wildfires contribute to the incidence of coccidioidomycosis, an emerging fungal disease in the Western United States with sharp increases in incidence observed since 2000. While coccidioidomycosis outbreaks have occurred among wildland firefighters clearing brush, it remains unknown whether fires are associated with an increased incidence among the general population. Methods: We identified 19 wildfires occurring within California's highly endemic San Joaquin Valley between 2003 and 2015. Using geolocated surveillance records, we applied a synthetic control approach to estimate the effect of each wildfire on the incidence of coccidioidomycosis among residents that lived within a hexagonal buffer of 20 km radii surrounding the fire. Results: We did not detect excess cases due to wildfires in the 12 months (pooled estimated percent change in cases: 2.8%; 95% confidence interval [CI] = -29.0, 85.2), 13-24 months (7.9%; 95% CI = -27.3, 113.9), or 25-36 months (17.4%; 95% CI = -25.1, 157.1) following a wildfire. When examined individually, we detected significant increases in incidence following three of the 19 wildfires, all of which had relatively large adjacent populations, high transmission before the fire, and a burn area exceeding 5,000 acres. Discussion: We find limited evidence that wildfires drive increases in coccidioidomycosis incidence among the general population. Nevertheless, our results raise concerns that large fires in regions with ongoing local transmission of Coccidioides may be associated with increases in incidence, underscoring the need for field studies examining Coccidioides spp. in soils and air pre- and post-wildfires.

Predicting the public health impact of bivalent vaccines and nirmatrelvir-ritonavir against COVID-19.

Background: Uptake of COVID-19 bivalent vaccines and oral medication nirmatrelvir-ritonavir (Paxlovid) has remained low across the United States. Assessing the public health impact of increasing uptake of these interventions in key risk groups can guide further public health resources and policy. Methods: This modeling study used person-level data from the California Department of Public Health on COVID-19 cases, hospitalizations, deaths, and vaccine administration from July 23, 2022 to January 23, 2023. We modeled the impact of additional uptake of bivalent COVID-19 vaccines and nirmatrelvir-ritonavir during acute illness in different risk groups defined by age (50+, 65+, 75+ years) and vaccination status (everyone, primary series only, previously vaccinated). We predicted the number of averted COVID-19 cases, hospitalizations, and deaths and number needed to treat (NNT). Results: For both bivalent vaccines and nirmatrelvir-ritonavir, the most efficient strategy (based on NNT) for averting severe COVID-19 was targeting the 75+ years group. We predicted that perfect coverage of bivalent boosters in the 75+ years group would avert 3,920 hospitalizations (95%UI: 2,491-4,882; 7.8% total averted; NNT 387) and 1,074 deaths (95%UI: 774-1,355; 16.2% total averted; NNT 1,410). Perfect uptake of nirmatrelvir-ritonavir in the 75+ years group would avert 5,644 hospitalizations (95%UI: 3,947-6,826; 11.2% total averted; NNT 11) and 1,669 deaths (95%UI: 1,053-2,038; 25.2% total averted; NNT 35). Conclusions: These findings suggest prioritizing uptake of bivalent boosters and nirmatrelvir-ritonavir among the oldest age groups would be efficient and have substantial public health impact in reducing the burden of severe COVID-19, but would not address the entire burden of severe COVID-19.

Assessing the accuracy of California county level COVID-19 hospitalization forecasts to inform public policy decision making.

BACKGROUND: The COVID-19 pandemic has highlighted the role of infectious disease forecasting in informing public policy. However, significant barriers remain for effectively linking infectious disease forecasts to public health decision making, including a lack of model validation. Forecasting model performance and accuracy should be evaluated retrospectively to understand under which conditions models were reliable and could be improved in the future. METHODS: Using archived forecasts from the California Department of Public Health's California COVID Assessment Tool ( https://calcat.covid19.ca.gov/cacovidmodels/ ), we compared how well different forecasting models predicted COVID-19 hospitalization census across California counties and regions during periods of Alpha, Delta, and Omicron variant predominance. RESULTS: Based on mean absolute error estimates, forecasting models had variable performance across counties and through time. When accounting for model availability across counties and dates, some individual models performed consistently better than the ensemble model, but model rankings still differed across counties. Local transmission trends, variant prevalence, and county population size were informative predictors for determining which model performed best for a given county based on a random forest classification analysis. Overall, the ensemble model performed worse in less populous counties, in part because of fewer model contributors in these locations. CONCLUSIONS: Ensemble model predictions could be improved by incorporating geographic heterogeneity in model coverage and performance. Consistency in model reporting and improved model validation can strengthen the role of infectious disease forecasting in real-time public health decision making.