This paper demonstrates how the combustion of fossil fuels for transport purpose might cause health implications. Based on an original case study [i.e. the Hubei province in China, the epicentre of the coronavirus disease-2019 (COVID-19) pandemic], we collected data on atmospheric pollutants (PM2.5, PM10 and CO2) and economic growth (GDP), along with daily series on COVID-19 indicators (cases, resuscitations and deaths). Then, we adopted an innovative Machine Learning approach, applying a new image Neural Networks model to investigate the causal relationships among economic, atmospheric and COVID-19 indicators. Empirical findings emphasise that any change in economic activity is found to substantially affect the dynamic levels of PM2.5, PM10 and CO2 which, in turn, generates significant variations in the spread of the COVID-19 epidemic and its associated lethality. As a robustness check, the conduction of an optimisation algorithm further corroborates previous results.

Risky sexual behaviour (RSB) is defined as behaviours leading to sexually transmitted diseases and unintended pregnancies. According to the Joint United Nations Program on HIV/AIDS, HIV infection was very high among adolescents and youths living in sub-Saharan Africa including Ethiopia. This study was aimed to assess the prevalence of RSB and associated factors among undergraduate students at the University of Gondar.

An institution-based cross-sectional study was conducted from June to July 2019 and a simple random sampling technique was employed to select 420 students. Data were collected using a structured self-administered questionnaire, entered into Epi-info version 7.0 and exported to Statistical Package for Social Sciences (SPSS) version 25 for analysis, and presented in frequencies, percentages and tables. Bivariable and multivariable logistic regression analysis were carried out to identify variables having significant association with RSB.

The prevalence of RSB among undergraduate students at the University of Gondar was 44.0%. Age [adjusted odds ratio (AOR): 2.12; 95% confidence interval (CI) (1.19–3.79)], residence [AOR: 2.14; 95% CI (1.22–3.75)], living arrangement [AOR: 9.79; 95% CI (5.34–17.9)], daily religious attendance[AOR: 0.57; 95% CI (0.33–0.99)], drink alcohol [AOR: 9.19; 95% CI (3.74–22.59)] and having information about reproductive health and sexually transmitted diseases [AOR:3.05; 95% CI (1.00–9.27)] were factors significantly associated with RSB.

Nearly half of the respondents engaged in risky sexual activity. This prevalence is high and the students are at high risk of exposure to sexually transmitted diseases that need reproductive health intervention like counselling and discussion. Creating awareness is needed for the students regarding reproductive health and the risk of sexually transmitted diseases. In addition, giving special attention is required for students who use alcohol, who did not live with family and who have urban residence.

Hand hygiene (HH) performance on entering intensive care units (ICUs) is commonly accepted but often inadequately performed. We developed a simple, inexpensive module that connects touchless dispensers of alcohol sanitiser (TDAS) to the automatic doors of a paediatric ICU, and assessed the impact of this intervention on HH compliance of hospital staff and visitors. A prospective observational study was conducted over a 3-week period prior to the intervention, followed by a 4-week period post intervention. HH performance was monitored by a research assistant whose office location enabled direct and video-assisted observation of the ICU entrance. A total of 609 entries to the ICU was recorded. Overall HH performance was 46.9% (92/196) before and 98.5% (406/413) after the intervention. Our findings suggest that HH performance on entering an ICU can be improved via a mechanism that makes operation of an automatic door dependent on use of a TDAS system, and thus contribute to infection control.

Helicobacter pylori eradication therapy was included with insurance coverage from 1999 onwards in Japan, with the incidence of peptic ulcer expected to decrease as a consequence. This study investigated the temporal dynamics of peptic ulcer in Japan and identified underlying contributory factors using mathematical models. We investigated the seroprevalence of H. pylori and analysed a snapshot of peptic ulcer cases. Ten statistical models that incorporated important events – H. pylori infection, the cohort effect, eradication therapy and the natural trend for reduction – were fitted to the case data. The hazard of infection with H. pylori was extracted from published estimates. Models were compared using the Akaike information criterion (AIC), and factor contributions were quantified using the coefficient of determination. The best-fit model indicated that 88.1% of the observed snapshot of cases (AIC = 289.2) included the effects of (i) H. pylori infection, (ii) the cohort effect and (iii) eradication therapy, as explanatory variables, the contributions of which were 80.8%, 4.0% and 3.2%, respectively. Among inpatients, a simpler model with (i) H. pylori infection only was favoured (AIC = 107.7). The time-dependent epidemiological dynamics of peptic ulcers were captured and H. pylori infection and eradication therapy explained ⩾84% of the dramatic decline in peptic ulcer occurrence.

At present, there is scarce evidence about the burden associated with the isolation of COVID-19 patients. We aimed to assess the differences between COVID-19 and other influenza-like illnesses (ILIs) in disease burden brought by isolation. We conducted an online survey of 302 respondents who had COVID-19 or other ILIs and compared the burden of isolation due to sickness with one-to-one propensity score matching. The primary outcomes are the duration and productivity losses associated with isolation, the secondary outcome is the health-related quality of life (HRQoL) valuation on the day of the survey. Acute symptoms of outpatient COVID-19 and other ILIs lasted 17 (interquartile range (IQR) 9–32) and 7 (IQR 4–10) days, respectively. The length of isolation due to COVID-19 was 18 (IQR 10–33) days and that due to other ILIs was 7 (IQR 4–11) days, respectively. The monetary productivity loss of isolation due to COVID-19 was 1424.3 (IQR 825.6–2545.5) USD and that due to other ILIs was 606.1 (IQR 297.0–1090.9) USD, respectively. HRQoL at the time of the survey was lower in the COVID-19 group than in the ‘other ILIs’ group (0.89 and 0.96, P = 0.001). COVID-19 infection imposes a substantial disease burden, even in patients with non-severe disease. This burden is larger for COVID-19 than other ILIs, mainly because the required isolation period is longer.

Enterotoxigenic Escherichia coli (ETEC) strains that express various fimbrial or nonfimbrial colonisation factors (CFs) and enterotoxins are critical causes of diarrhoeal diseases. Human ETEC serotype O169:H41 (O169) has been a representative of epidemic ETEC worldwide; the organism shows massive adherence to HEp-2 cells similar to enteroaggregative E. coli. Previously, we determined the complete sequence of the unstable virulence plasmid, pEntYN10. The plasmid included a unique set of genes encoding a novel CF resembling K88 (F4) of porcine ETEC, in addition to CS6, a well-known representative CF of human ETEC, and another novel CF similar to CS8 (CFA/III) of human ETEC. In the present study, we focused on K88-like CF (hereafter, K88O169) that may allow the organisms to infect domestic livestock like original K88-harbouring strains that can cause diarrhoea in piglets. Samples were tested for antibodies against recombinant proteins of possible paralogous adhesins, FaeG1 and FaeG2, from K88O169 and the FaeG of typical K88 (F4). The seroepidemiological study using recombinant antigens (two paralogs FaeG1 and FaeG2 from K88O169) showed reactivity of porcine (18.0%) and bovine (17.1%) sera to K88O169 FaeG1 and/or FaeG2 antigens on indirect ELISA tests. These results suggest that E. coli with K88O169 adhesin can infect various hosts, including pigs and cattle. This is the first report of domestic livestock having antibodies to K88O169 of human ETEC. Although human ETEC had been thought to be distinguished from those of domestic animals based on CFs, zoonotic strains may conceal themselves among human ETEC organisms. The concept of One Health should be adopted to intervene in ETEC infections among animals and humans.

To achieve the elimination of the hepatitis C virus (HCV), sustained and sufficient levels of HCV testing is critical. The purpose of this study was to assess trends in testing and evaluate the effectiveness of strategies to diagnose people living with HCV. Data were from 12 primary care clinics in Victoria, Australia, that provide targeted services to people who inject drugs (PWID), alongside general health care. This ecological study spanned 2009–2019 and included analyses of trends in annual numbers of HCV antibody tests among individuals with no previous positive HCV antibody test recorded and annual test yield (positive HCV antibody tests/all HCV antibody tests). Generalised linear models estimated the association between count outcomes (HCV antibody tests and positive HCV antibody tests) and time, and χ2 test assessed the trend in test yield. A total of 44 889 HCV antibody tests were conducted 2009–2019; test numbers increased 6% annually on average [95% confidence interval (CI) 4–9]. Test yield declined from 2009 (21%) to 2019 (9%) (χ2P = <0.01). In more recent years (2013–2019) annual test yield remained relatively stable. Modest increases in HCV antibody testing and stable but high test yield within clinics delivering services to PWID highlights testing strategies are resulting in people are being diagnosed however further increases in the testing of people at risk of HCV or living with HCV may be needed to reach Australia's HCV elimination goals.

This study aimed to describe the incidence of Streptococcus bovis/Streptococcus equinus complex (SBSEC) bacteremia, distribution of the SBSEC subspecies, and their respective association with colorectal cancer (CRC). A population-based retrospective cohort study of all episodes of SBSEC-bacteremia from 2003 to 2018 in Skåne Region, Sweden. Subspecies was determined by whole-genome sequencing. Medical charts were reviewed. The association between subspecies and CRC were analysed using logistic regression. In total 266 episodes of SBSEC-bacteremia were identified and the average annual incidence was 2.0 per 100 000 inhabitants. Of the 236 isolates available for typing, the most common subspecies was S. gallolyticus subsp. pasteurianus 88/236 (37%) followed by S. gallolyticus subsp. gallolyticus 58/236 (25%). In order to determine the risk of cancer following bacteremia, an incidence cohort of 174 episodes without a prior diagnosis of CRC or metastasised cancer was followed for 560 person-years. CRC was found in 13/174 (7%), of which 9 (69%) had S. gallolyticus subsp. gallolyticus-bacteremia. In contrast to other European studies, S. gallolyticus subsp. pasteurianus was the most common cause of SBSEC-bacteremia. CRC diagnosis after bacteremia was strongly associated with S. gallolyticus subsp. gallolyticus-bacteremia. Identification of SBSEC subspecies can guide clinical decision-making regarding CRC work-up following bacteremia.

Identification of societal activities associated with SARS-CoV-2 infection may provide an evidence base for implementing preventive measures. Here, we investigated potential determinants for infection in Denmark in a situation where society was only partially open. We conducted a national matched case-control study. Cases were recent RT-PCR test-positives, while controls, individually matched on age, sex and residence, had not previously tested positive for SARS-CoV-2. Questions concerned person contact and community exposures. Telephone interviews were performed over a 7-day period in December 2020. We included 300 cases and 317 controls and determined odds ratios (ORs) and 95% confidence intervals (95% CI) by conditional logistical regression with adjustment for household size and country of origin. Contact (OR 4.9, 95% CI 2.4–10) and close contact (OR 13, 95% CI 6.7–25) with a person with a known SARS-CoV-2 infection were main determinants. Contact most often took place in the household or work place. Community determinants included events with singing (OR 2.1, 95% CI 1.1–4.1), attending fitness centres (OR 1.8, 95% CI 1.1–2.8) and consumption of alcohol in a bar (OR 10, 95% CI 1.5–65). Other community exposures appeared not to be associated with infection, these included shopping at supermarkets, travel by public transport, dining at restaurants and private social events with few participants. Overall, the restrictions in place at the time of the study appeared to be sufficient to reduce transmission of disease in the public space, which instead largely took place following direct exposures to people with known SARS-CoV-2 infections.

The early identification and prediction of hand-foot-and-mouth disease (HFMD) play an important role in the disease prevention and control. However, suitable models are different in regions due to the differences in geography, social economy factors. We collected data associated with daily reported HFMD cases and weather factors of Zibo city in 2010~2019 and used the generalised additive model (GAM) to evaluate the effects of weather factors on HFMD cases. Then, GAM, support vectors regression (SVR) and random forest regression (RFR) models are used to compare predictive results. The annual average incidence was 129.72/100 000 from 2010 to 2019. Its distribution showed a unimodal trend, with incidence increasing from March, peaking from May to September. Our study revealed the nonlinear relationship between temperature, rainfall and relative humidity and HFMD cases and based on the predictive result, the performances of three models constructed ranked in descending order are: SVR > GAM> RFR, and SVR has the smallest prediction errors. These findings provide quantitative evidence for the prediction of HFMD for special high-risk regions and can help public health agencies implement prevention and control measures in advance.

The aim of our study was to determine the distribution of hepatitis B virus (HBV) genotypes and subgenotypes in ethnic minorities in Yunnan province to provide evidence supporting the theoretical basis for hepatitis B prevention and control. We obtained serum samples and demographic data from 765 individuals reported by Yunnan province who had either acute or chronic HBV infection and were from one of 20 ethnic minority populations: Achang, Bai, Brown, Tibetan, Dai, Deang, Dulong, Hani, Hui, Jingpo, Lahu, Yi, Lisu Miao, Naxi, Nu, Pumi, Wa, Yao, or Zhuang people. We sequenced the HBV DNA and determined the genotypes and subgenotypes of the isolated HBVs. We mapped the genotype and subgenotype distribution by ethnic minority population and conducted descriptive analyses. There were four genotypes among the 20 ethnic groups: genotype B (21.3% of samples), C (76.6%), D (1.8%) and I (0.3%). The most common subgenotype was C1. There were no genotype differences by gender (P = 0.954) or age (P = 0.274), but there were differences by region (P < 0.001). There were differences in genotype distribution (P < 0.001) and subgenotype distribution (P = 0.011) by ethnic group. Genotype D was most prominent in Tibet and most HBV isolates were C/D recombinant viruses. The only two genotype I virus isolates were in Zhuang people. Susceptibility and geographic patterns may influence HBV prevalence in different ethnic populations, but additional research is needed for such a determination.

Phenomenological models are popular for describing the epidemic curve. We present how they can be used at different phases in the epidemic, by modelling the daily number of new hospitalisations (or cases). As real-time prediction of the hospital capacity is important, a joint model of the new hospitalisations, number of patients in hospital and in intensive care unit (ICU) is proposed. This model allows estimation of the length of stay in hospital and ICU, even if no (or limited) individual level information on length of stay is available. Estimation is done in a Bayesian framework. In this framework, real-time alarms, defined as the probability of exceeding hospital capacity, can be easily derived. The methods are illustrated using data from the COVID-19 pandemic in March–June 2020 in Belgium, but are widely applicable.

This paper proposes and analyses a stochastic model for the spread of an infectious disease transmitted between clients and care workers in the UK domiciliary (home) care setting. Interactions between clients and care workers are modelled using specially generated networks, with network parameters reflecting realistic patterns of care needs and visit allocation. These networks are then used to simulate a susceptible-exposed-infected-recovered/dead (SEIR/D)-type epidemic dynamics with different numbers of infectious and recovery stages. The results indicate that with the same overall capacity provided by care workers, the minimum peak proportion of infection and the smallest overall size of infection are achieved for the highest proportion of overlap between visit allocation, i.e. when care workers have the highest chances of being allocated a visit to the same client they have visited before. An intuitive explanation of this is that while providing the required care coverage, maximising overlap in visit allocation reduces the possibility of an infectious care worker inadvertently spreading the infection to other clients. The model is generic and can be adapted to any directly transmitted infectious disease, such as, more recently, corona virus disease 2019, provided accurate estimates of disease parameters can be obtained from real data.

Vulnerability to coronavirus disease (COVID)-19 varies due to differences in interferon gamma (IFNγ) immunity. We investigated whether a key modifiable interferon precursor, interleukin-18, was related to COVID-19, overall and by severity, using Mendelian randomisation. We used four established genome-wide significant genetic predictors of interleukin-18 applied to the most recent genome-wide association study of COVID-19 (June 2021) to obtain Mendelian randomisation inverse variance weighted estimates by severity, i.e. any (cases = 112 612, non-cases = 2 474 079), hospitalised (cases = 24 274, non-cases = 2 061 529) and very severe (cases = 8779, non-cases = 1 001 875) COVID-19. To be comprehensive, we also conducted an exploratory analysis for IFNγ and two related cytokines with less well-established genetic predictors, i.e. interleukin-12 and interleukin-23. Genetically predicted interleukin-18 was associated with lower risk of any COVID-19 (odds ratio (OR) 0.96 per standard deviation, 95% confidence interval (0.94–0.99, P-value 0.004)) and of very severe COVID-19 (OR 0.88, 95% CI 0.78–0.999, P-value 0.048). Sensitivity analysis and a more liberal genetic instrument selection gave largely similar results. Few genome-wide significant genetic predictors were available for IFNγ, interleukin-12 or interleukin-23, and no associations with COVID-19 were evident. Interleukin-18 could be a modifiable target to prevent COVID-19 and should be further explored in an experimental design.

Cyclospora cayetanensis is an emerging food- and waterborne pathogen that causes cyclosporiasis, a gastrointestinal disease in humans. The parasite is endemic in tropical and subtropical regions; however, its prevalence is largely dependent on environmental factors, such as climate and rainfall patterns. The objective of this paper was to conduct a systematic review and meta-analysis to determine the prevalence of C. cayetanensis in water and to determine if geography, water source and other variables influence this prevalence. A literature search was performed using search terms relating to water and C. cayetanensis in MEDLINE®, CAB Direct, Food Science and Technology Abstracts, Agricola databases and Environmental Science Index. Observational studies published in English after 1979 were eligible. Screening, data extraction and risk-of-bias assessment were performed independently by two reviewers. A multi-level random-effects meta-analysis was completed to determine the prevalence of C. cayetanensis in water and subgroup meta-analyses were performed to explore between-study heterogeneity. The search identified 828 unique articles, and after the screening, 33 articles were included in the review. The pooled prevalence of C. cayetanensis in water was 6.90% [95% confidence interval (CI) 2.25%–13.05%, I2 = 84.38%]. Subgroup meta-analyses revealed significant differences in the prevalence between continents. Additionally, laboratory methods between studies were highly variable and these findings highlight the need for further environmental research on C. cayetanensis in water using detection methods that include PCR and sequencing to accurately identify the organism. The results of this study can be used to help assess the risk of waterborne cyclosporiasis.

Leafy green vegetables are a common source of Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) foodborne illness outbreaks. Ruminant animals, primarily cattle, are the major reservoir of STEC O157. Epidemiological, traceback and field investigations were conducted to identify potential outbreak sources. Product and environmental samples were tested for STEC. A reoccurring strain of STEC O157 caused two multistate outbreaks linked to romaine lettuce in 2018 and 2019, resulting in 234 illnesses in 33 states. Over 80% of patients interviewed consumed romaine lettuce before illness. The romaine lettuce was sourced from two California growing regions: Santa Maria and Salinas Valley in 2018 and Salinas Valley in 2019. The outbreak strain was isolated from environmental samples collected at sites >90 miles apart across growing regions, as well as from romaine-containing products in 2019. Although the definitive route of romaine contamination was undetermined, use of a contaminated agricultural water reservoir in 2018 and contamination from cattle grazing on adjacent land in 2019 were suspected as possible factors. Preventing lettuce contamination from growth to consumption is imperative to preventing illness. These outbreaks highlight the need to further understand mechanisms of romaine contamination, including the role of environmental or animal reservoirs for STEC O157.

It is unclear if – after symptom onset of a primary case of coronavirus disease-2019 (COVID-19) in a household – ensuing chains of transmissions among household members occur and if household epidemiology of COVID-19 is modified by the different circulating variants. We analysed data of 52 774 household clusters to investigate the day of symptom onset of ensuing cases in households relative to the symptom onset of the primary case within the household. Irrespective of cluster size or age of the primary case, 95% of all secondary household cases had symptom onset within 14 days after the symptom onset of the primary case. Stratification by variant showed that the mean interval from symptom onset of the primary case to the symptom onset of secondary cases decreased significantly from 4.8 days (wildtype) to 4.5 days (alpha) and 4.0 days (delta). Similarly, the cumulative proportion of 95% of secondary cases occurred within 14 days (wild type), 12 days (alpha) and 10 days (delta). Our findings suggest that during dominant delta circulation – apart from rare individual constellations – a 10-day household quarantine after symptom onset of the primary case is sufficient for household contacts who remain COVID-free.

Nosocomial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreaks among health care workers have been scarcely reported so far. This report presents the results of an epidemiologic and molecular investigation of a SARS-CoV-2 outbreak among laundromat facility workers in a large tertiary centre in Israel. Following the first three reported cases of SARS-CoV-2 among laundromat workers, all 49 laundromat personnel were screened by qRT-PCR tests using naso- and oropharingeal swabs. Epidemiologic investigations included questionnaires, interviews and observations of the laundromat facility. Eleven viral RNA samples were then sequenced, and a phylogenetic analysis was performed using MEGAX.

The integrated investigation defined three genetic clusters and helped identify the index cases and the assumed routes of transmission. It was then deduced that shared commute and public showers played a role in SARS-CoV-2 transmission in this outbreak, in addition to improper PPE use and social gatherings (such as social eating and drinking). In this study, we present an integrated epidemiologic and molecular investigation may help detect the routes of SARS-CoV-2 transmission, emphasising such routes that are less frequently discussed. Our work reinforces the notion that person-to-person transmission is more likely to cause infections than environmental contamination (e.g. from handling dirty laundry).

This study investigated the characteristics of transmission routes of COVID-19 cluster infections (⩾10 linked cases within a short period) in Gangwon Province between 22 February 2020 and 31 May 2021. Transmission routes were divided into five major categories and 35 sub-categories according to the relationship between the infector and the infectee and the location of transmission. A total of 61 clusters occurred during the study period, including 1741 confirmed cases (55.7% of all confirmed cases (n = 3125)). The the five major routes of transmission were as follows: ‘using (staying in) the same facility (50.7%), ‘cohabiting family members’ (23.3%), ‘social gatherings with acquaintances’ (10.8%), ‘other transmission routes’ (7.0%), and ‘social gatherings with non-cohabiting family members/relatives’ (5.5%). For transmission caused by using (staying in) the same facility, the highest number of confirmed cases was associated with churches, followed by medical institutions (inpatient), sports facilities, military bases, offices, nightlife businesses, schools, restaurants, day-care centres and kindergarten, and service businesses. Our analysis highlights specific locations with frequent transmission of infections, and transmission routes that should be targeted in situations where adherence to disease control rules is difficult.

Serosurveillance is an important epidemiologic tool for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), used to estimate infection rates and the degree of population immunity. There is no general agreement on which antibody biomarker(s) should be used, especially with the rollout of vaccines globally. Here, we used random forest models to demonstrate that a single spike or receptor-binding domain (RBD) antibody was adequate for classifying prior infection, while a combination of two antibody biomarkers performed better than any single marker for estimating time-since-infection. Nucleocapsid antibodies performed worse than spike or RBD antibodies for classification, but can be useful for estimating time-since-infection, and in distinguishing infection-induced from vaccine-induced responses. Our analysis has the potential to inform the design of serosurveys for SARS-CoV-2, including decisions regarding a number of antibody biomarkers measured.