Identifying outbreaks in sewer networks: An adaptive sampling scheme under network's uncertainty.

Motivated by the implementation of a SARS-Cov-2 sewer surveillance system in Chile during the COVID-19 pandemic, we propose a set of mathematical and algorithmic tools that aim to identify the location of an outbreak under uncertainty in the network structure. Given an upper bound on the number of samples we can take on any given day, our framework allows us to detect an unknown infected node by adaptively sampling different network nodes on different days. Crucially, despite the uncertainty of the network, the method allows univocal detection of the infected node, albeit at an extra cost in time. This framework relies on a specific and well-chosen strategy that defines new nodes to test sequentially, with a heuristic that balances the granularity of the information obtained from the samples. We extensively tested our model in real and synthetic networks, showing that the uncertainty of the underlying graph only incurs a limited increase in the number of iterations, indicating that the methodology is applicable in practice.

Monitoring progress towards the elimination of hepatitis C as a public health threat in Norway: a modelling study among people who inject drugs and immigrants.

BACKGROUND: The global incidence target for the elimination of hepatitis C among people who inject drugs (PWID) is <2/100. In Norway, the hepatitis C epidemic is concentrated in PWID. Immigrants are the second most important risk group for chronic infection. We modelled the incidence of hepatitis C among active PWID, and the prevalence of chronic infection among active PWID, ex-PWID and immigrants in Norway until 2022. METHODS: We built a stochastic compartmental model, which was informed using data from national data sources, literature, and expert opinion. We report median values with 95% credible intervals (CrI). RESULTS: The model estimated 30 (95% Crl: 13-52) new infections among active PWID in 2022, or 0.37/100 (95% Crl: 0.17-0.65), down from a peak of 726 (95% Crl: 506-1,067) in 2000. Across all groups, the model estimated 3,202 (95% Crl: 1,273-6,601) chronically infected persons in 2022. Results were robust in sensitivity analyses. CONCLUSIONS: Norway provides an example of the feasibility of hepatitis C elimination in a setting with a concentrated epidemic, high coverage of harm reduction services and no treatment restrictions. Continued momentum is needed to further reduce the transmission and burden of hepatitis C in Norway.

Electronic Health Record Data for Lyme Disease Surveillance, Massachusetts, USA, 2017-2018.

Lyme disease surveillance based on provider and laboratory reports underestimates incidence. We developed an algorithm for automating surveillance using electronic health record data. We identified potential Lyme disease markers in electronic health record data (laboratory tests, diagnosis codes, prescriptions) from January 2017-December 2018 in 2 large practice groups in Massachusetts, USA. We calculated their sensitivities and positive predictive values (PPV), alone and in combination, relative to medical record review. Sensitivities ranged from 57% (95% CI 47%-69%) for immunoassays to 87% (95% CI 70%-100%) for diagnosis codes. PPVs ranged from 53% (95% CI 43%-61%) for diagnosis codes to 58% (95% CI 50%-66%) for immunoassays. The combination of a diagnosis code and antibiotics within 14 days or a positive Western blot had a sensitivity of 100% (95% CI 86%-100%) and PPV of 82% (95% CI 75%-89%). This algorithm could make Lyme disease surveillance more efficient and consistent.

Crimean-Congo Hemorrhagic Fever Virus Seroprevalence in Human and Livestock Populations, Northern Tanzania.

We conducted a cross-sectional study of Crimean-Congo hemorrhagic fever virus (CCHFV) in northern Tanzania. CCHFV seroprevalence in humans and ruminant livestock was high, as were spatial heterogeneity levels. CCHFV could represent an unrecognized human health risk in this region and should be included as a differential diagnosis for febrile illness.

Development and Evaluation of Surveillance System for Identifying Jail-Associated COVID-19 Cases in Minnesota, USA, 2022.

Confinement facilities are high-risk settings for the spread of infectious disease, necessitating timely surveillance to inform public health action. To identify jail-associated COVID-19 cases from electronic laboratory reports maintained in the Minnesota Electronic Disease Surveillance System (MEDSS), Minnesota, USA, the Minnesota Department of Health developed a surveillance system that used keyword and address matching (KAM). The KAM system used a SAS program (SAS Institute Inc., https://www.sas.com) and an automated program within MEDSS to identify confinement keywords and addresses. To evaluate KAM, we matched jail booking data from the Minnesota Statewide Supervision System by full name and birthdate to the MEDSS records of adults with COVID-19 for 2022. The KAM system identified 2,212 cases in persons detained in jail; sensitivity was 92.40% and specificity was 99.95%. The success of KAM demonstrates its potential to be applied to other diseases and congregate-living settings for real-time surveillance without added reporting burden.

Month-to-month all-cause mortality forecasting: a method allowing for changes in seasonal patterns.

Forecasting of seasonal mortality patterns can provide useful information for planning health-care demand and capacity. Timely mortality forecasts are needed during severe winter spikes and/or pandemic waves to guide policy-making and public health decisions. In this article, we propose a flexible method for forecasting all-cause mortality in real time considering short-term changes in seasonal patterns within an epidemiologic year. All-cause mortality data have the advantage of being available with less delay than cause-specific mortality data. In this study, we use all-cause monthly death counts obtained from the national statistical offices of Denmark, France, Spain, and Sweden from epidemic seasons 2012-2013 through 2021-2022 to demonstrate the performance of the proposed approach. The method forecasts deaths 1 month ahead, based on their expected ratio to the next month. Prediction intervals are obtained via bootstrapping. The forecasts accurately predict the winter mortality peaks before the COVID-19 pandemic. Although the method predicts mortality less accurately during the first wave of the COVID-19 pandemic, it captures the aspects of later waves better than other traditional methods. The method is attractive for health researchers and governmental offices for aiding public health responses because it uses minimal input data, makes simple and intuitive assumptions, and provides accurate forecasts both during seasonal influenza epidemics and during novel virus pandemics.

Human biomonitoring without in-person interaction: public health engagements during the COVID-19 pandemic and future implications.

BACKGROUND: Public health initiatives, including human biomonitoring, have been impacted by unique challenges since the onset of the COVID-19 pandemic, compounding a decades-long trend of declining public participation. To combat low public participation rates, public health professionals often employ extensive engagement approaches including in-person interactions related to enrollment and sampling, success of which is an essential component of a statistically defensible study. The onset of the COVID-19 pandemic challenged public health programs to diversify engagement and sampling approaches, limiting direct interactions for the health and safety of the population. This study explores biomonitoring recruitment strategies through non-contact mechanisms and evaluate the application feasibility for population-based studies. METHODS: The Iowa Biomonitoring Program at the State Hygienic Laboratory developed a human biomonitoring study that utilized a multifaceted, distance-based approach. Traditional techniques, such as mailed recruitment invitations and phone-based discussions, were coupled with internet-based surveys and self-collected, shipped urine and water samples. Participation rates were evaluated by employing different mailing methods, and the demographics of enrolled participants were examined. RESULTS: This non-human contact approach achieved a nearly 14% participation rate among a rural population, well above our target rates. Our improved mailing strategy for targeting initially unresponsive participants yielded a significantly increase in the participation rates. The respondents were predominantly individuals with educational attainment of at least high school level. Among all the eligible participants, 83% submitted self-collected samples, a rate comparable to the National Health and Nutrition Examination Survey which involved in-person interviews. CONCLUSIONS: The practice of engaging a rural population during the COVID-19 pandemic by transitioning from face-to-face interactions to a combination of mailing and internet-based approaches resulted in higher-than-expected participant recruitment and sample collection rates. Given the declining trend in the response rates for population-based survey studies, our results suggest conducting human biomonitoring without direct human interaction is feasible, which provides further opportunity to improve response rates and the relevance and reach of public health initiatives.

Addressing Critical Barriers for Sustainability of Asthma Stock Inhaler Policy Implementation and Resultant Programming.

BACKGROUND: Asthma is a prevalent health concern among Illinois children and management is significantly influenced by social determinants. Seventeen states have adopted stock inhaler laws, but implementation varies widely. OBJECTIVE: To assess critical barriers to implementation and address sustainability of stock inhaler programming in school-based asthma care in IL. METHODS: Semi-structured interviews were conducted with high asthma burden school districts in IL to assess barriers in implementing stock inhaler policies and resultant programming. Thematic analysis was performed, using Atlas.ti to identify and code "threats" to future sustainability. Data was synthesized and presented to stakeholders for barrier mitigation. A schematic flow chart outlining steps to support sustainability was created. RESULTS: Eighteen interviews were conducted with key community partners across eight Illinois school districts, representing rural, urban, and suburban areas. Analysis revealed 25 barriers, with several identified as "threats" to future sustainability, including liability concerns, follow-up care assurance, funding/resources, pharmacy dispensing practices, district-level readiness to change, and nurse staffing. Stakeholders formed a statewide coalition to address these barriers, increase awareness, plan evaluations, and advise on state funding allocation. A national stock inhaler toolkit tailored to school administrative needs was developed to support sustainability efforts. CONCLUSION: Strategic stakeholder and community engagement are vital for establishing and sustaining stock inhaler programs that adhere to policy mandates. Many districts face challenges initiating and maintaining such programs without critical barrier mitigation and support. Collaborative solutions are necessary to ensure effective school-based asthma management and mitigate persistent pediatric asthma health disparities.

Community testing practices for autism within the autism and developmental disabilities monitoring network.

BACKGROUND: No data exist at the population level on what tests are used to aid in the diagnosis of autism spectrum disorder in community practice. OBJECTIVES: To describe autism spectrum disorder testing practices to inform autism spectrum disorder identification efforts. METHODS: Data are from the Autism and Developmental Disabilities Monitoring Network, a multi-site surveillance system reporting prevalence estimates and characteristics of 8-year-old children with autism spectrum disorder. Percentages of children with autism spectrum disorder who received any autism spectrum disorder test or a 'gold standard' test were calculated by site, sex, race, median household income, and intellectual ability status. Risk ratios were calculated to compare group differences. RESULTS: Of 5058 8-year-old children with autism spectrum disorder across 11 sites, 3236 (64.0%) had a record of any autism spectrum disorder test and 2136 (42.2%) had a 'gold standard' ADOS or ADI-R test. Overall, 115 children (2.3%) had both the ADOS and ADI-R in their records. Differences persisted across race, median household income, and intellectual ability status. Asian/Pacific Islander children had the highest percent receiving any ASD test (71.8%; other groups range: 57.4-66.0%) and White children had the highest percent receiving 'gold standard' tests (46.4%; other groups range: 35.6-43.2%). Children in low-income neighbourhoods had a lower percent of any test (62.5%) and 'gold standard' tests (39.4%) compared to medium (70.2% and 47.5%, respectively) and high (69.6% and 46.8%, respectively) income neighbourhoods. Children with intellectual disability had a lower percent of any ASD test (81.7%) and 'gold standard' tests (52.6%) compared to children without intellectual disability (84.0% and 57.6%, respectively). CONCLUSIONS: Autism spectrum disorder testing practices vary widely by site and differ by race and presence of co-occurring intellectual disability, suggesting opportunities to standardise and/or improve autism spectrum disorder identification practices.

Syndromic case definitions for lower respiratory tract infection (LRTI) are less sensitive in older age: an analysis of symptoms among hospitalised adults.

BACKGROUND: Lower Respiratory Tract Infections (LRTI) pose a serious threat to older adults but may be underdiagnosed due to atypical presentations. Here we assess LRTI symptom profiles and syndromic (symptom-based) case ascertainment in older (≥ 65y) as compared to younger adults (< 65y). METHODS: We included adults (≥ 18y) with confirmed LRTI admitted to two acute care Trusts in Bristol, UK from 1st August 2020- 31st July 2022. Logistic regression was used to assess whether age ≥ 65y reduced the probability of meeting syndromic LRTI case definitions, using patients' symptoms at admission. We also calculated relative symptom frequencies (log-odds ratios) and evaluated how symptoms were clustered across different age groups. RESULTS: Of 17,620 clinically confirmed LRTI cases, 8,487 (48.1%) had symptoms meeting the case definition. Compared to those not meeting the definition these cases were younger, had less severe illness and were less likely to have received a SARS-CoV-2 vaccination or to have active SARS-CoV-2 infection. Prevalence of dementia/cognitive impairment and levels of comorbidity were lower in this group. After controlling for sex, dementia and comorbidities, age ≥ 65y significantly reduced the probability of meeting the case definition (aOR = 0.67, 95% CI:0.63-0.71). Cases aged ≥ 65y were less likely to present with fever and LRTI-specific symptoms (e.g., pleurisy, sputum) than younger cases, and those aged ≥ 85y were characterised by lack of cough but frequent confusion and falls. CONCLUSIONS: LRTI symptom profiles changed considerably with age in this hospitalised cohort. Standard screening protocols may fail to detect older and frailer cases of LRTI based on their symptoms.

COVID-19 outbreaks surveillance through text mining applied to electronic health records.

BACKGROUND: The COVID-19 pandemic has caused significant disruptions to everyday life and has had social, political, and financial consequences that will persist for years. Several initiatives with intensive use of technology were quickly developed in this scenario. However, technologies that enhance epidemiological surveillance in contexts with low testing capacity and healthcare resources are scarce. Therefore, this study aims to address this gap by developing a data science model that uses routinely generated healthcare encounter records to detect possible new outbreaks early in real-time. METHODS: We defined an epidemiological indicator that is a proxy for suspected cases of COVID-19 using the health records of Emergency Care Unit (ECU) patients and text mining techniques. The open-field dataset comprises 2,760,862 medical records from nine ECUs, where each record has information about the patient's age, reported symptoms, and the time and date of admission. We also used a dataset where 1,026,804 cases of COVID-19 were officially confirmed. The records range from January 2020 to May 2022. Sample cross-correlation between two finite stochastic time series was used to evaluate the models. RESULTS: For patients with age 18 years, we find time-lag () = 72 days and cross-correlation () ~ 0.82, = 25 days and ~ 0.93, and = 17 days and ~ 0.88 for the first, second, and third waves, respectively. CONCLUSIONS: In conclusion, the developed model can aid in the early detection of signs of possible new COVID-19 outbreaks, weeks before traditional surveillance systems, thereby anticipating in initiating preventive and control actions in public health with a higher likelihood of success.

Demographic characteristics, perinatal smoking patterns, and risk for neonatal health complications among pregnant smokers in the United States who begin using electronic cigarettes during pregnancy: A descriptive study using population-based surveillance data.

INTRODUCTION: Health agencies have called for research evaluating e-cigarette (EC) use in supporting prenatal smoking cessation. This study aimed to describe (a) characteristics of smokers who begin using ECs during pregnancy, (b) how frequently smokers reduce or eliminate pre- and post-natal combustible cigarette (CC) use, and (c) risk for neonatal health complications among smokers who initiate ECs during pregnancy. METHODS: Pregnant women using CCs exclusively pre-pregnancy, who participated in a U.S. surveillance study, were classified by their reported late-pregnancy smoking behavior as CC-exclusive users, EC initiators, or quitters. EC initiators were further subclassified as dual users (used both ECs and CCs) or EC replacers (used ECs exclusively). RESULTS: Of 29,505 pregnant smokers, 1.5% reported using ECs during the last 3 pregnancy months. Among them, 29.7% became EC-exclusive users. EC initiators were disproportionately non-Hispanic White. Relative to quitters, EC initiators had lower income, were less likely to be married, have intended pregnancies, receive first-trimester prenatal care, and participate in a federal assistance program. Compared to CC-exclusive users, EC initiators overall, and dual users specifically, were more likely to reduce pre- and post-natal CC usage relative to pre-pregnancy levels. EC initiators' risk for neonatal health complications fell between quitters and CC-exclusive users, though differences were not statistically significant. CONCLUSIONS: Although EC initiators reduced CC use more than CC-exclusive users, only 29.7% reported complete CC cessation, and there was insufficient evidence of reduction in neonatal health complications relative to CC-exclusive users. Currently, ECs should not be considered a viable gestational smoking cessation strategy. IMPLICATIONS: Health agencies have identified a critical need for research evaluating the use of e-cigarettes in supporting prenatal smoking cessation. Using the US Pregnancy Risk Assessment Monitoring System surveillance study data, we provide real-world evidence that prenatal e-cigarette initiation as a smoking cessation tool is used infrequently among pregnant combustible cigarettes smokers. Most using e-cigarettes in the last three months of pregnancy also used combustible cigarettes.

Agricultural activities and risk of Alzheimer's disease: the TRACTOR project, a nationwide retrospective cohort study.

Data regarding Alzheimer's disease (AD) occurrence in farming populations is lacking. This study aimed to investigate whether, among the entire French farm manager (FM) workforce, certain agricultural activities are more strongly associated with AD than others, using nationwide data from the TRACTOR (Tracking and monitoring occupational risks in agriculture) project. Administrative health insurance data (digital electronic health/medical records and insurance claims) for the entire French agricultural workforce, over the period 2002-2016, on the entire mainland France were used to estimate the risk of AD for 26 agricultural activities with Cox proportional hazards model. For each analysis (one for each activity), the exposed group included all FMs that performed the activity of interest (e.g. crop farming), while the reference group included all FMs who did not carry out the activity of interest (e.g. FMs that never farmed crops between 2002 and 2016). There were 5067 cases among 1,036,069 FMs who worked at least one year between 2002 and 2016. Analyses showed higher risks of AD for crop farming (hazard ratio (HR) = 3.72 [3.47-3.98]), viticulture (HR = 1.29 [1.18-1.42]), and fruit arboriculture (HR = 1.36 [1.15-1.62]). By contrast, lower risks of AD were found for several animal farming types, in particular for poultry and rabbit farming (HR = 0.29 [0.20-0.44]), ovine and caprine farming (HR = 0.50 [0.41-0.61]), mixed dairy and cow farming (HR = 0.46 [0.37-0.57]), dairy farming (HR = 0.67 [0.61-0.73]), and pig farming (HR = 0.30 [0.18-0.52]). This study shed some light on the association between a wide range of agricultural activities and AD in the entire French FMs population.

Health Hazard Evaluations of occupational cancer cluster concerns: the USA, January 2001-December 2020.

OBJECTIVES: To describe recent investigations of potential workplace cancer clusters. METHODS: We identified Health Hazard Evaluations (HHEs) of cancer concerns during 2001-2020. We described information about industry, requestors, cancer characteristics, investigative procedures, and determinations about the presence of a cluster (ie, presence of excess cases, unusual case distribution or exposure). RESULTS: Of 5754 HHEs, 174 included cancer concerns, comprising 1%-5% of HHEs per year. In 123 HHEs, the cancer cluster concerns involved different cancer primary sites. Investigation procedures varied but included record review (n=63, 36%) and site visits (n=22, 13%). Of 158 HHEs with a cluster determination by investigator(s), 151 (96%) were not considered cancer clusters. In seven HHEs, investigators found evidence of a cluster, but occupational exposure to a carcinogen was not identified. CONCLUSIONS: The proportion of HHEs on workplace cancer cluster concerns remained steady over time; most did not meet the definition of a cluster or uncover an occupational cause. Public health practitioners can use this information to provide updated context when addressing workplace cancer cluster concerns and as motivation to refine investigative approaches. More broadly, this review highlights an opportunity to identify best practices on how to apply community cluster investigation methods to the workplace.

Ovarian cancer deaths attributable to asbestos exposure in Lombardy (Italy) in 2000-2018.

OBJECTIVES: We aimed to estimate the fraction of deaths from ovarian cancer attributable to asbestos exposure in Lombardy Region, Italy, using a novel approach that exploits the fact that ovarian cancer asbestos exposure is associated with pleural cancer and other risk factors for breast cancer. METHODS: This ecological study is based on the Italian National Institute of Statistics mortality data. We formulate a trivariate Bayesian joint disease model to estimate the attributable fraction (AF) and the number of ovarian cancer deaths attributable to asbestos exposure from the geographic distribution of ovarian, pleural and breast cancer mortality at the municipality level from 2000 to 2018. Expected deaths and standardised mortality ratios were calculated using regional rates. RESULTS: We found shared dependencies between ovarian and pleural cancer, which capture risk factors common to the two diseases (asbestos exposure), and a spatially structured clustering component shared between ovarian and breast cancer, capturing other risk factors. Based on 10 462 ovarian cancer deaths, we estimated that 574 (95% credibility interval 388-819) were attributable to asbestos (AF 5.5%; 95% credibility interval 3.7-7.8). AF reaches 34%-47% in some municipalities with known heavy asbestos pollution. CONCLUSIONS: The impact of asbestos on ovarian cancer occurrence can be relevant, particularly in areas with high asbestos exposure. Estimating attributable cases was possible only by using advanced Bayesian modelling to consider other risk factors for ovarian cancer. These findings are instrumental in tailoring public health surveillance programmes and implementing compensation and prevention policies.

Legionnaires' disease in transportation, construction and other occupations in 39 US jurisdictions, 2014-2016.

BACKGROUND: Certain workers are at increased risk for acquiring Legionnaires' disease compared with other workers. This study aims to identify occupations at increased risk for acquiring Legionnaires' disease. METHODS: Using data from the US Centers for Disease Control and Prevention's Supplemental Legionnaires' Disease Surveillance System, this study identified Legionnaires' disease confirmed patients ≥16 years of age in 39 states with reported symptom onset during 2014-2016. Age-adjusted and sex-adjusted incidence rate ratios (IRR) stratified by occupation group were calculated by comparing Legionnaires' disease patients in an occupation group (eg, transportation) to those in all other occupation groups (eg, non-transportation). RESULTS: A total of 2553 patients had a known occupation group. The two occupations with the highest burden were transportation (N=287; IRR=2.11) and construction (N=269; IRR=1.82). Truck drivers comprised the majority (69.7%) of the transportation occupation group and construction labourers comprised almost half (49%) of the construction occupation group. The healthcare support occupation had the highest IRR (N=75; IRR=2.16). CONCLUSION: Transportation and construction workers, who are generally not covered by guidance related to building water systems, have increased risk of Legionnaires' disease compared with other workers. One hypothesised risk factor for truck drivers is the use of non-genuine windshield cleaner in their vehicles. A simple intervention is to use genuine windshield cleaner with bactericidal properties (ie, includes isopropanol/methanol) which can reduce the risk of Legionella growth and transmission. To improve surveillance of Legionnaires' disease and identification of similar exposures, the authors encourage the collection of occupation and industry information for all patients with Legionnaires' disease.

Outbreak of lead poisoning from a civilian indoor firing range in the UK.

INTRODUCTION: Lead exposure from discharged lead dust is a recognised risk at firing ranges. We report a lead poisoning outbreak among staff and their close contacts at a UK civilian indoor 24 m firing range. METHODS: A retrospective review was undertaken of data collected on all patients at risk of lead poisoning identified either by direct referral to the Clinical Toxicology clinicians at the West Midlands Poisons Unit, or via the Trace Elements Supra-Regional Assay Service Laboratory at Sandwell hospital. RESULTS: Eighty-seven patients were identified as having possible lead exposure, either at the firing range or via close contacts. Of these, 63 patients aged between 6 months and 78 years attended for blood lead concentration (BLC) testing. The highest BLC at presentation was 11.7 µmol/L (242 µg/dL). Only nine patients reported any symptoms at presentation. Fifteen patients received lead chelation therapy with oral dimercaptosuccinic acid (or succimer) 30 mg/kg/day or intravenous sodium calcium edetate (EDTA) 75 mg/kg/day, dependent on stock availability. DISCUSSION: This report highlights the need for vigilance of lead poisoning as an occupational hazard in the UK, including at recreational facilities such as indoor firing ranges. It emphasises the importance of regulation of lead exposure in the workplace, particularly given the vague symptoms of lead poisoning, and proposes re-appraisal of UK legislation. This report also highlights potential issues surrounding stock availability of rarely used antidotes for uncommon presentations in the event of an outbreak of poisoning.

Farming activity and risk of treated thyroid disorders: Insights from the TRACTOR project, a nationwide cohort study.

BACKGROUND: Epidemiological data regarding thyroid diseases are lacking, in particular for occupationally exposed populations. OBJECTIVES: To compare the risk of hypothyroidism and hyperthyroidism between farming activities within the complete population of French farm managers (FMs). METHODS: Digital health data from retrospective administrative databases, including insurance claims and electronic health/medical records, was employed. This cohort data spanned the entirety of French farm managers (FMs) who had undertaken work at least once from 2002 to 2016. Survival analysis with the time to initial medication reimbursement as timescale was used to examine the association (hazard ratio, HR) between 26 specific farming activities and both treated hypothyroidism and hyperthyroidism. A distinct model was developed for each farming activity, comparing FMs who had never engaged in the specific farming activity between 2002 and 2016 with those who had. All analyses were adjusted for potential confounders (e.g., age), and sensitivity analyses were conducted. RESULTS: Among 1088561 FMs (mean age 46.6 [SD 14.1]; 31% females), there were 31834 hypothyroidism cases (75% females) and 620 hyperthyroidism cases (67% females), respectively. The highest risks were observed for cattle activities for both hyperthyroidism (HR ranging from 1.75 to 2.42) and hypothyroidism (HR ranging from 1.41 to 1.44). For hypothyroidism, higher risks were also observed for several animal farming activities (pig, poultry, and rabbit), as well as fruit arboriculture (HR = 1.22 [1.14-1.31]). The lowest risks were observed for activities involving horses. Sex differences in the risk of hypothyroidism were observed for eight activities, with the risk being higher for males (HR = 1.09 [1.01-1.20]) than females in viticulture (HR = 0.97 [0.93-1.00]). The risk of hyperthyroidism was two times higher for male dairy farmers than females. DISCUSSION: Our findings offer a comprehensive overview of thyroid disease risks within the FM community. Thyroid ailments might not stem from a single cause but likely arise from the combined effects of various causal agents and triggering factors (agricultural exposome). Further investigation into distinct farming activities-especially those involving cattle-is essential to pinpoint potential risk factors that could enhance thyroid disease monitoring in agriculture.

PFOA and testis cancer in the Veneto Region (Italy).

The largest documented episode of human contamination by PFOA in the world (approximately 150,000 actual residents on 1 January 2020) has occurred in Italy's Veneto Region. In this large, mostly flat plain area, a cluster of testicular cancers has also been observed. Preliminary data are reported, and the most relevant and recent recommendations regarding the health surveillance of exposed individuals are emphasized.

Influence of sociodemographic and obstetric factors on maternal mortality in Brazil from 2011 to 2021.

BACKGROUND: Obstetric causes are classified as direct (complications of pregnancy, childbirth or the puerperium) or indirect (caused by pregnancy but not directly caused by it). This study aimed to analyze maternal mortality from obstetric causes in Brazil from 2011 to 2021. METHODS: This was an ecological study on mortality and live births. The outcomes were the specific risk of mortality from direct and indirect cause adjustment and death during pregnancy and the puerperium. Binary and multiple linear logistic regressions were used to assess the influence of sociodemographic factors and maternal and child health indicators on maternal mortality and time of death (pregnancy and puerperium). RESULTS: Regarding mortality during pregnancy and during the puerperium, increased (p = 0.003) and decreased (p = 0.004) mortality over the years, respectively; residing in the northern region was associated with lower (p < 0.05) and greater (p = 0.035) odds; and the Maternal Mortality Committee was the primary and least active source of investigation, respectively (p < 0.0001). The number of deaths from indirect causes increased with age (p < 0.001) and in the northern region (p = 0.011) and decreased in the white (< 0.05) and stable union (0.002) regions. Specifically, for mortality risk, the age group [women aged 15-19 years presented an increase in cesarean section (p < 0.001) was greater than that of women who had < 4 antenatal visits (p < 0.001)], education [women who completed high school (8 to 11 years) was greater when they had < 4 prenatal visits (p = 0.018)], and marital status [unmarried women had more than 4 antenatal visits (p < 0.001); cesarean birth (p = 0.010) and < 4 antenatal visits (p = 0.009) were predictors of marriage; and women in a stable union who had < 4 prenatal visits and live births to teenage mothers (p < 0.001) were predictors]. Women who had no education (p = 0.003), were divorced (p = 0.036), had cesarean deliveries (p < 0.012), or lived in the north or northeast (p < 0.008) had higher indirect specific mortality risk. CONCLUSIONS: Sociodemographic factors and maternal and child health indicators were related to different patterns of obstetric mortality. Obstetric mortality varied by region, marital status, race, delivery, prenatal care, and cause of death.