Disease risks from foods, England and Wales, 1996-2000.

Data from population-based studies and national surveillance systems were collated and analyzed to estimate the impact of disease and risks associated with eating different foods in England and Wales. From 1996 to 2000, an estimated 1,724,315 cases of indigenous foodborne disease per year resulted in 21,997 hospitalizations and 687 deaths. The greatest impact on the healthcare sector arose from foodborne Campylobacter infection (160,788 primary care visits and 15,918 hospitalizations), while salmonellosis caused the most deaths (209). The most important cause of indigenous foodborne disease was contaminated chicken (398,420 cases, risk [cases/million servings] = 111; case-fatality rate [deaths/100,000 cases] = 35, deaths = 141). Red meat (beef, lamb, and pork) contributed heavily to deaths, despite lower levels of risk (287,485 cases, risk = 24, case-fatality rate = 57, deaths = 164). Reducing the impact of indigenous foodborne disease is mainly dependent on controlling the contamination of chicken

Factors Associated With Measles Transmission in the United States During the Postelimination Era.

Importance: Measles cases and outbreaks continue to occur in the United States after the introduction of measles from endemic settings. Objective: To discern the factors associated with measles transmission in the United States after measles had been eliminated. Design, Setting, and Participants: This cross-sectional study was conducted from January 1, 2001, to December 31, 2017, in the United States among US residents and international visitors with confirmed measles. A maximum likelihood algorithm that uses the observed dates of rash onset and the known distribution of the serial interval (time between symptom onset in related consecutive cases) was applied to outbreak notification data to estimate the effective reproduction number (R), or the mean number of new infections generated per case. Transmissibility was assessed by comparing R based on the characteristics of primary and secondary cases of measles. Exposures: Measles virus. Main Outcomes and Measures: Effective reproduction number (R), or the mean number of successful transmission events per case of measles (ie, the mean number of persons to whom each patient with measles spreads measles). Results: A total of 2218 individuals with confirmed measles cases (1025 female, 1176 male, and 17 sex not reported; median age, 15 years [range, 0-89 years]) reported from 2001 to 2017 were evaluated. Among patients who received no doses of measles vaccine, R was 0.76 (95% CI, 0.71-0.81); among patients who received 1 dose of measles vaccine, R was 0.17 (95% CI, 0.11-0.26); among patients who received 2 doses or more of measles vaccine, R was 0.27 (95% CI, 0.17-0.39); and among patients with unknown vaccination status, R was 0.52 (95% CI, 0.44-0.60). Among patients born before 1957, R was 0.35 (95% CI, 0.20-0.58), and among those born on or after 1957, R was 0.64 (95% CI, 0.61-0.68). R was higher when primary and secondary cases of measles were patients aged 5 to 17 years (0.36 [95% CI, 0.31-0.42]) compared with assortative transmission in other age groups (<1 year, 0.14 [95% CI, 0.10-0.20]; 1-4 years, 0.25 [95% CI, 0.20-0.30]; 18-29 years, 0.19 [95% CI, 0.15-0.24]; 30-49 years, 0.15 [95% CI, 0.11-0.20]; ≥50 years, 0.04 [95% CI, 0.01-0.10]). Conclusions and Relevance: The findings of this study support having high targets for 2-dose measles vaccine coverage, particularly among school-aged children in the United States

Risk for Fomite-Mediated Transmission of SARS-CoV-2 in Child Daycares, Schools, Nursing Homes, and Offices.

Severe acute respiratory syndrome coronavirus 2 can persist on surfaces, suggesting possible surface-mediated transmission of this pathogen. We found that fomites might be a substantial source of transmission risk, particularly in schools and child daycares. Combining surface cleaning and decontamination with mask wearing can help mitigate this risk

Electronic Outbreak Surveillance in Germany: A First Evaluation for Nosocomial Norovirus Outbreaks

BACKGROUND: In Germany, surveillance for infectious disease outbreaks is integrated into an electronic surveillance system. For 2007, the national surveillance database contains case-based information on 201,224 norovirus cases, three-quarters of which are linked to outbreaks. We evaluated the data quality of the national database in reflecting nosocomial norovirus outbreak (NNO) data available in 19 Hessian local public health authorities (LPHAs) and the influence of differences between LPHA's follow-up procedures for laboratory notifications of Norovirus positive stool samples on outbreak underascertainment. METHODS: Data on NNO beginning in 2007 and notified to the 19 LPHAs were extracted from the national database, investigated regarding internal validity and compared to data collected from LPHAs for a study on NNO control. LPHAs were questioned whether they routinely contacted all persons for whom a laboratory diagnosis of norovirus infection was notified. The number of outbreaks per 1,000 hospital beds and the number of cases within NNOs for acute care and rehabilitation hospitals were compared between counties with and without complete follow-up. RESULTS: The national database contained information on 155 NNOs, including 3,115 cases. Cases were missed in the national database in 58 (37%) of the outbreaks. Information on hospitalisation was incorrect for an estimated 47% of NNO cases. Information on county of infection was incorrect for 24% (199/820) of cases being forwarded between LPHAs for data entry. Reported NNO incidence and number of NNO cases in acute care hospitals was higher in counties with complete follow-up (incidence-rate ratio (IRR) 2.7, 95% CI 1.4-5.7, p-value 0.002 and IRR 2.1, 95% CI 1.9-2.4, p-value 0.001, respectively). CONCLUSIONS: Many NNOs are not notified by hospitals and differences in LPHA procedures have an impact on the number of outbreaks captured in the surveillance system. Forwarding of case-by-case data on Norovirus outbreak cases from the local to the state and national level should not be required

Infrequent Transmission of Monovalent Human Rotavirus Vaccine Virus to Household Contacts of Vaccinated Infants in Malawi

Horizontal transmission of rotavirus vaccine virus may contribute to indirect effects of rotavirus vaccine, but data are lacking from low-income countries. Serial stool samples were obtained from Malawian infants who received 2 doses of monovalent human rotavirus vaccine (RV1) (days 4, 6, 8, and 10 after vaccination) and from their household contacts (8-10 days after vaccine). RV1 vaccine virus in stool was detected using semiquantitative real-time reverse-transcription polymerase chain reaction. RV1 fecal shedding was detected in 41 of 60 vaccinated infants (68%) and in 2 of 147 household contacts (1.4%). Horizontal transmission of vaccine virus within households is unlikely to make a major contribution to RV1 indirect effects in Malawi

Factors influencing the decision to receive seasonal influenza vaccination among US corporate non-healthcare workers

Influenza causes significant mortality and morbidity in the United States (US). Employees are exposed to influenza at work and can spread it to others. The influenza vaccine is safe, effective, and prevents severe outcomes; however, coverage among US adults (50.2%) is below Healthy People 2030 target of 70%. These highlights need for more effective vaccination promotion interventions. Understanding predictors of vaccination acceptance could inform vaccine promotion messages, improve coverage, and reduce illness-related work absences. We aimed to identify factors influencing influenza vaccination among US non-healthcare workers. Using mixed-methods approach, we evaluated factors influencing influenza vaccination among employees in three US companies during April-June 2020. Survey questions were adapted from the WHO seasonal influenza survey. Most respondents (n = 454) were women (272, 59.9%), 20-39 years old (n = 250, 55.1%); white (n = 254, 56.0%); had a college degree (n = 431, 95.0%); and reported receiving influenza vaccine in preceding influenza season (n = 297, 65.4%). Logistic regression model was statistically significant, X (16, N = 450) = 31.6, p = .01. Education [(OR) = 0.3, 95%CI = 0.1-0.6)] and race (OR = 0.4, 95%CI = 0.2-0.8) were significant predictors of influenza vaccine acceptance among participants. The majority had favorable attitudes toward influenza vaccination and reported that physician recommendation would influence their vaccination decisions. Seven themes were identified in qualitative analysis: "Protecting others" (109, 24.0%), "Protecting self" (105, 23.1%), "Vaccine accessibility" (94, 20.7%), "Education/messaging" (71, 15.6%), "Policies/requirements" (15, 3.3%), "Reminders" (9, 2.0%), and "Incentives" (3, 0.7%). Our findings could facilitate the development of effective influenza vaccination promotion messages and programs for employers, and workplace vaccination programs for other diseases such as COVID-19, by public health authorities

Two Epidemiologic Patterns of Norovirus Outbreaks: Surveillance in England and Wales, 1992–2000

In the period 1992–2000, the Public Health Laboratory Service Communicable Disease Surveillance Centre collected standardized epidemiologic data on 1,877 general outbreaks of Norovirus (formerly “Norwalk-like virus”) infection in England and Wales. Seventy-nine percent of general outbreaks occurred in health-care institutions, i.e., hospitals (40%) and residential-care facilities (39%). When compared with outbreaks in other settings, those in health-care institutions were unique in exhibiting a winter peak (p<0.0001); these outbreaks were also associated with significantly higher death rates and prolonged duration but were smaller in size and less likely to be foodborne. These data suggest that Norovirus infection has considerable impact on the health service and the vulnerable populations residing in institutions such as hospitals and residential homes. A distinct outbreak pattern in health-care institutions suggests a combination of host, virologic, and environmental factors that mediate these divergent epidemiologic patterns

Association of enteropathogen detection with diarrhoea by age and high versus low child mortality settings: a systematic review and meta-analysis

BACKGROUND: The odds ratio (OR) comparing pathogen presence in diarrhoeal cases versus asymptomatic controls is a measure for diarrhoeal disease cause that has been integrated into burden of disease estimates across diverse populations. This study aimed to estimate the OR describing the association between pathogen detection in stool and diarrhoea for 15 common enteropathogens by age group and child mortality setting. METHODS: We did a systematic review to identify case-control and cohort studies published from Jan 1, 1990, to July 9, 2019, which examined at least one enteropathogen of interest and the outcome diarrhoea. The analytical dataset included data extracted from published articles and supplemented with data from the Global Enteric Multicenter Study and the Malnutrition and Enteric Disease study. Random effects meta-analysis models were fit for each enteropathogen, stratified by age group and child mortality level, and adjusted for pathogen detection method and study design to produce summary ORs describing the association between pathogen detection in stool and diarrhoea. FINDINGS: 1964 records were screened and 130 studies (over 88 079 cases or diarrhoea samples and 135 755 controls or non-diarrhoea samples) were available for analysis. Heterogeneity (I2) in unadjusted models was substantial, ranging from 27·6% to 86·6% across pathogens. In stratified and adjusted models, summary ORs varied by age group and setting, ranging from 0·4 (95% CI 0·2-0·6) for Giardia lamblia to 54·1 (95% CI 7·4-393·5) for Vibrio cholerae. INTERPRETATION: Incorporating effect estimates from diverse data sources into diarrhoeal disease cause and burden of disease models is needed to produce more representative estimates. FUNDING: WHO, Bill & Melinda Gates Foundation, and National Institutes of Health

Global diarrhoea-associated mortality estimates and models in children: Recommendations for dataset and study selection

BACKGROUND: Multiple factors contribute to variation in disease burden, including the type and quality of data, and inherent properties of the models used. Understanding how these factors affect mortality estimates is crucial, especially in the context of public health decision making. We examine how the quality of the studies selected to provide mortality data, influence estimates of burden and provide recommendations about the inclusion of studies and datasets to calculate mortality estimates. METHODS: To determine how mortality estimates are affected by the data used to generate model outputs, we compared the studies used by The Institute of Health Metrics and Evaluation (IHME) and Maternal and Child Epidemiology Estimation (MCEE) modelling groups to generate enterotoxigenic Escherichia coli (ETEC) and Shigella-associated mortality estimates for 2016. Guided by an expert WHO Working Group, we applied a modified Newcastle-Ottawa Scale (NOS) to evaluate the quality of studies used by both modelling groups. RESULTS: IHME and MCEE used different sets of ETEC and Shigella studies in their models and the majority of studies were high quality. The distribution of the NOS scores was similar between the two modelling groups. We observed an overrepresentation of studies from some countries in SEAR, AFR and WPR compared to other WHO regions. CONCLUSION: We identified key differences in study inclusion and exclusion criteria used by IHME and MCEE and discuss their impact on datasets used to generate diarrhoea-associated mortality estimates. Based on these observations, we provide a set of recommendations for future estimates of mortality associated with enteric diseases

Modeling missing cases and transmission links in networks of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africa

Patterns of transmission of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases worldwide in 2017. Modeling TB transmission networks can provide insight into drivers of transmission, but incomplete sampling of TB cases can pose challenges for inference from individual epidemiologic and molecular data. We assessed the effect of missing cases on a transmission network inferred from Mycobacterium tuberculosis sequencing data on extensively drug-resistant TB cases in KwaZulu-Natal, South Africa, diagnosed in 2011–2014. We tested scenarios in which cases were missing at random, missing differentially by clinical characteristics, or missing differentially by transmission (i.e., cases with many links were under- or oversampled). Under the assumption that cases were missing randomly, the mean number of transmissions per case in the complete network needed to be larger than 20, far higher than expected, to reproduce the observed network. Instead, the most likely scenario involved undersampling of high-transmitting cases, and models provided evidence for super-spreading. To our knowledge, this is the first analysis to have assessed support for different mechanisms of missingness in a TB transmission study, but our results are subject to the distributional assumptions of the network models we used. Transmission studies should consider the potential biases introduced by incomplete sampling and identify host, pathogen, or environmental factors driving super-spreading.This work was presented at the Seventh International Conference on Infectious Disease Dynamics (Epidemics7), Charleston, South Carolina, December 3–6, 2019.The National Institute of Allergy and Infectious Diseases, US National Institutes of Health, the National Institute of Allergy and Infectious Diseases, the Emory Center for AIDS Research, the Einstein Center for AIDS Research and the Einstein/Montefiore Institute for Clinical and Translational Research.https://academic.oup.com/ajehj2021Medical Microbiolog