Although handwashing is an effective way to prevent infections, there is scarce evidence on predictors of handwashing during a pandemic. This paper aims to identify behavioural and demographic predictors of handwashing. The study surveyed 674 adults in Malaysia in May 2020 regarding whether the time spent on social media predicted handwashing contingent on gender and number of children. More time spent on social media was positively associated with handwashing for males with three or more children. However, for males without children, social media use was negatively associated with handwashing. The association was not significant for males with one or two children. For females, more time spent on social media was significantly linked to more handwashing only for females with one child. Gender, a traditional predictor of handwashing, was a useful predictor only for those who spent more than three hours per day on social media and had at most one child. Number of children was a novel negative predictor for males who did not use social media and who averaged one hour per day on social media, a positive predictor for males who spent lots of time on social media, but not a predictor for females. In sum, social media use predicts handwashing, and is thus a helpful variable for use in targeted health communication during a pandemic – particularly through social media. Further, more conventional predictors like gender and number of children exhibit contingency effects with social media use.

Diverse risk factors intercede the outcomes of coronavirus disease 2019 (COVID-19). We conducted this retrospective cohort study with a cohort of 1016 COVID-19 patients diagnosed in May 2020 to identify the risk factors associated with morbidity and mortality outcomes. Data were collected by telephone-interview and reviewing records using a questionnaire and checklist. The study identified morbidity and mortality risk factors on the 28th day of the disease course. The majority of the patients were male (64.1%) and belonged to the age group 25–39 years (39.4%). Urban patients were higher in proportion than rural (69.3% vs. 30.7%). Major comorbidities included 35.0% diabetes mellitus (DM), 28.4% hypertension (HTN), 16.6% chronic obstructive pulmonary disease (COPD), and 7.8% coronary heart disease (CHD). The morbidity rate (not-cured) was 6.0%, and the mortality rate (non-survivor) was 2.5%. Morbidity risk factors included elderly (AOR = 2.56, 95% CI = 1.31–4.99), having comorbidity (AOR = 1.43, 95% CI = 0.83–2.47), and smokeless tobacco use (AOR = 2.17, 95% CI = 0.84–5.61). The morbidity risk was higher with COPD (RR = 2.68), chronic kidney disease (CKD) (RR = 3.33) and chronic liver disease (CLD) (RR = 3.99). Mortality risk factors included elderly (AOR = 7.56, 95% CI = 3.19–17.92), having comorbidity (AOR = 5.27, 95% CI = 1.88–14.79) and SLT use (AOR = 1.93, 95% CI = 0.50–7.46). The mortality risk was higher with COPD (RR = 7.30), DM (RR = 2.63), CHD (RR = 4.65), HTN (RR = 3.38), CKD (RR = 9.03), CLD (RR = 10.52) and malignant diseases (RR = 9.73). We must espouse programme interventions considering the morbidity and mortality risk factors to condense the aggressive outcomes of COVID-19.

Deaths are frequently under-estimated during emergencies, times when accurate mortality estimates are crucial for emergency response. This study estimates excess all-cause, pneumonia and influenza mortality during the coronavirus disease 2019 (COVID-19) pandemic using the 11 September 2020 release of weekly mortality data from the United States (U.S.) Mortality Surveillance System (MSS) from 27 September 2015 to 9 May 2020, using semiparametric and conventional time-series models in 13 states with high reported COVID-19 deaths and apparently complete mortality data: California, Colorado, Connecticut, Florida, Illinois, Indiana, Louisiana, Massachusetts, Michigan, New Jersey, New York, Pennsylvania and Washington. We estimated greater excess mortality than official COVID-19 mortality in the U.S. (excess mortality 95% confidence interval (CI) 100 013–127 501 vs. 78 834 COVID-19 deaths) and 9 states: California (excess mortality 95% CI 3338–6344) vs. 2849 COVID-19 deaths); Connecticut (excess mortality 95% CI 3095–3952) vs. 2932 COVID-19 deaths); Illinois (95% CI 4646–6111) vs. 3525 COVID-19 deaths); Louisiana (excess mortality 95% CI 2341–3183 vs. 2267 COVID-19 deaths); Massachusetts (95% CI 5562–7201 vs. 5050 COVID-19 deaths); New Jersey (95% CI 13 170–16 058 vs. 10 465 COVID-19 deaths); New York (95% CI 32 538–39 960 vs. 26 584 COVID-19 deaths); and Pennsylvania (95% CI 5125–6560 vs. 3793 COVID-19 deaths). Conventional model results were consistent with semiparametric results but less precise. Significant excess pneumonia deaths were also found for all locations and we estimated hundreds of excess influenza deaths in New York. We find that official COVID-19 mortality substantially understates actual mortality, excess deaths cannot be explained entirely by official COVID-19 death counts. Mortality reporting lags appeared to worsen during the pandemic, when timeliness in surveillance systems was most crucial for improving pandemic response.

A Canadian outbreak investigation into a cluster of Escherichia coli O121 was initiated in late 2016. When initial interviews using a closed-ended hypothesis-generating questionnaire did not point to a common source, cases were centrally re-interviewed using an open-ended approach. The open-ended interviews led cases to describe exposures with greater specificity, as well as food preparation activities. Data collected supported hypothesis generation, particularly with respect to flour exposures. In March 2017, an open sample of Brand X flour from a case home, and a closed sample collected at retail of the same brand and production date, tested positive for the outbreak strain of E. coli O121. In total, 76% (16/21) of cases reported that they used or probably used Brand X flour or that it was used or probably was used in the home during their exposure period. Crucial hypothesis-generating techniques used during the course of the investigation included a centralised open-ended interviewing approach and product sampling from case homes. This was the first outbreak investigation in Canada to identify flour as the source of infection.

Previous research on respiratory infection transmission among university students has primarily focused on influenza. In this study, we explore potential transmission events for multiple respiratory pathogens in a social contact network of university students. University students residing in on-campus housing (n = 590) were followed for the development of influenza-like illness for 10-weeks during the 2012–13 influenza season. A contact network was built using weekly self-reported contacts, class schedules, and housing information. We considered a transmission event to have occurred if students were positive for the same pathogen and had a network connection within a 14-day period. Transmitters were individuals who had onset date prior to their infected social contact. Throat and nasal samples were analysed for multiple viruses by RT-PCR. Five viruses were involved in 18 transmission events (influenza A, parainfluenza virus 3, rhinovirus, coronavirus NL63, respiratory syncytial virus). Transmitters had higher numbers of co-infections (67%). Identified transmission events had contacts reported in small classes (33%), dormitory common areas (22%) and dormitory rooms (17%). These results suggest that targeting person-to-person interactions, through measures such as isolation and quarantine, could reduce transmission of respiratory infections on campus.

During the first months of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) epidemic in 2020, Spain implemented an initial lockdown period on 15 March followed by a strengthened lockdown period on 30 March when only essential workers continued to commute to work. However, little is known about the epidemic dynamics in different age groups during these periods.

We used the daily number of coronavirus 2019 cases (by date of symptom onset) reported to the National Epidemiological Surveillance Network among individuals aged 15–19 years through 65–69 years. For each age group g, we computed the proportion PrE(g) of individuals in age group g among all reported cases aged 15–69 years during the pre-lockdown period (1−10 March 2020) and the corresponding proportion PrL(g) during two lockdown periods (initial: 25 March−3 April; strengthened: 8–17 April 2020). For each lockdown period, we computed the proportion ratios PR(g) = PrL(g)/PrE(g). For each pair of age groups g1, g2, PR(g1)>PR(g2) implies a relative increase in the incidence of detected SARS-CoV-2 infection in the age group g1 compared with g2 for the lockdown period vs. the pre-lockdown period.

For the initial lockdown period, the highest PR values were in age groups 50–54 years (PR = 1.21; 95% CI: 1.12,1.30) and 55–59 years (PR = 1.19; 1.11,1.27). For the second lockdown period, the highest PR values were in age groups 15–19 years (PR = 1.26; 0.95,1.68) and 50–54 years (PR = 1.20; 1.09,1.31).

Our results suggest that different outbreak control measures led to different changes in the relative incidence by age group. During the initial lockdown period, when non-essential work was allowed, individuals aged 40–64 years, particularly those aged 50–59 years, had a higher relative incidence compared with the pre-lockdown period. Younger adults/older adolescents had an increased relative incidence during the later, strengthened lockdown. The role of different age groups during the epidemic should be considered when implementing future mitigation efforts.

When we consider a probability distribution about how many COVID-19-infected people will transmit the disease, two points become important. First, there could be super-spreaders in these distributions/networks and second, the Pareto principle could be valid in these distributions/networks regarding estimation that 20% of cases were responsible for 80% of local transmission. When we accept that these two points are valid, the distribution of transmission becomes a discrete Pareto distribution, which is a kind of power law. Having such a transmission distribution, then we can simulate COVID-19 networks and find super-spreaders using the centricity measurements in these networks. In this research, in the first we transformed a transmission distribution of statistics and epidemiology into a transmission network of network science and second we try to determine who the super-spreaders are by using this network and eigenvalue centrality measure. We underline that determination of transmission probability distribution is a very important point in the analysis of the epidemic and determining the precautions to be taken.

In this study, an analysis of the Chilean public health response to mitigate the spread of COVID-19 is presented. The analysis is based on the daily transmission rate (DTR). The Chilean response has been based on dynamic quarantines, which are established, lifted or prolonged based on the percentage of infected individuals in the fundamental administrative sections, called communes. This analysis is performed at a national level, at the level of the Metropolitan Region (MR) and at the commune level in the MR according to whether the commune did or did not enter quarantine between late March and mid-May of 2020. The analysis shows a certain degree of efficacy in controlling the pandemic using the dynamic quarantine strategy. However, it also shows that apparent control has only been partially achieved to date. With this policy, the control of the DTR partially falls to 4%, where it settles, and the MR is the primary vector of infection at the country level. For this reason, we can conclude that the MR has not managed to control the disease, with variable results within its own territory.

Determination of antibodies against ToRCH antigens at the beginning of pregnancy allows assessment of both the maternal immune status and the risks to an adverse pregnancy outcome. Age-standardised seroprevalences were determined in sera from 1009 women of childbearing age residing in Mexico, Brazil, Germany, Poland, Turkey or China using a multiparametric immunoblot containing antigen substrates for antibodies against Toxoplasma gondii, rubella virus, cytomegalovirus (CMV), herpes simplex viruses (HSV-1, HSV-2), Bordetella pertussis, Chlamydia trachomatis, parvovirus B19, Treponema pallidum and varicella zoster virus (VZV). Seroprevalences for antibodies against HSV-1 were >90% in samples from Brazil and Turkey, whereas the other four countries showed lower mean age-adjusted seroprevalences (range: 62.5–87.9%). Samples from Brazilian women showed elevated seroprevalences of antibodies against HSV-2 (40.1%), C. trachomatis (46.8%) and B. pertussis (56.6%) compared to the other five countries. Seroprevalences of anti-T. gondii antibodies (0.5%) and anti-parvovirus B19 antibodies (7.5%) were low in samples from Chinese women, compared to the other five countries. Samples from German women revealed a low age-standardised seroprevalence of anti-CMV antibodies (28.8%) compared to the other five countries. These global differences in immune status of women in childbearing age advocate country-specific prophylaxis strategies to avoid infection with ToRCH pathogens.

SARS-CoV-2, the causative agent of coronavirus disease 19 (COVID-19), was identified in Wuhan, China. Since then, the novel coronavirus started to be compared to influenza. The haematological parameters and inflammatory indexes are associated with severe illness in COVID-19 patients. In this study, the laboratory data of 120 COVID-19 patients, 100 influenza patients and 61 healthy controls were evaluated. Lower lymphocytes, eosinophils, basophils, platelets and higher delta neutrophil index (DNI), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) were found in COVID-19 and influenza groups compared to healthy controls. The eosinophils, lymphocytes and PLR made the highest contribution to differentiate COVID-19 patients from healthy controls (area under the curves (AUCs): 0.819, 0.817 and 0.716, respectively; P-value is <0.0001 for all). The NLR, the optimal cut-off value was 3.58, which resulted in a sensitivity of 30.8 and a specificity of 100 (AUC: 0.677, P < 0.0001). Higher leucocytes, neutrophils, DNI, NLR, PLR and lower lymphocytes, red blood cells, haemoglobin, haematocrit levels were found in severe patients at the end of treatment. Nonsevere patients showed an upward trend for lymphocytes, eosinophils and platelets, and a downward trend for neutrophils, DNI, NLR and PLR. However, there was an increasing trend for eosinophils, platelets and PLR in severe patients. In conclusion, NLR and PLR can be used as biomarkers to distinguish COVID-19 patients from healthy people and to predict the severity of COVID-19. The increasing value of PLR during follow-up may be more useful compared to NLR to predict the disease severity.

As the COVID-19 pandemic continues to escalate and place pressure on hospital system resources, a proper screening and risk stratification score is essential. We aimed to develop a risk score to identify patients with increased risk of COVID-19, allowing proper identification and allocation of limited resources. A retrospective study was conducted of 338 patients who were admitted to the hospital from the emergency room to regular floors and tested for COVID-19 at an acute care hospital in the Metropolitan Washington D.C. area. The dataset was split into development and validation sets with a ratio of 6:4. Demographics, presenting symptoms, sick contact, triage vital signs, initial laboratory and chest X-ray results were analysed to develop a prediction model for COVID-19 diagnosis. Multivariable logistic regression was performed in a stepwise fashion to develop a prediction model, and a scoring system was created based on the coefficients of the final model. Among 338 patients admitted to the hospital from the emergency room, 136 (40.2%) patients tested positive for COVID-19 and 202 (59.8%) patients tested negative. Sick contact with suspected or confirmed COVID-19 case (3 points), nursing facility residence (3 points), constitutional symptom (1 point), respiratory symptom (1 point), gastrointestinal symptom (1 point), obesity (1 point), hypoxia at triage (1 point) and leucocytosis (−1 point) were included in the prediction score. A risk score for COVID-19 diagnosis achieved area under the receiver operating characteristic curve of 0.87 (95% confidence interval (CI) 0.82–0.92) in the development dataset and 0.85 (95% CI 0.78–0.92) in the validation dataset. A risk prediction score for COVID-19 can be used as a supplemental tool to assist clinical decision to triage, test and quarantine patients admitted to the hospital from the emergency room.

The introduction of treatment and systematic vaccination has significantly reduced diphtheria mortality; however, toxigenic strains continue to circulate worldwide. The emergence of an indigenous diphtheria case with fatal outcome in Greece, after 30 years, raised challenges for laboratory confirmation, clinical and public health management. Toxigenic Corynebacterium diphtheriae was isolated from an incompletely vaccinated 8-year-old boy with underlying conditions. The child passed away due to respiratory distress syndrome, before the administration of diphtheria antitoxin (DAT). All close contacts in family, school and hospital settings were investigated. Pharyngeal swabs were obtained to determine asymptomatic carriage. Chemoprophylaxis was given for 7 days to all close contacts and a booster dose to those incompletely vaccinated. Testing revealed a classmate, belonging to a subpopulation group (Roma), and incompletely vaccinated, as an asymptomatic carrier with an indistinguishable toxigenic strain (same novel multilocus sequence type, designated ST698). This case highlights the role of asymptomatic carriage, as the entry of toxigenic strains into susceptible populations can put individuals and their environment at risk. Maintenance of high-level epidemiological and microbiological surveillance, implementation of systematic vaccination in children and adults with primary and booster doses, availability of a DAT stockpile, and allowing timely administration are the cornerstone to prevent similar incidents in the future.

Although the progression of invasive aspergillosis (IA) shares some risk factors in the development of active pulmonary tuberculosis (PTB), however, the prevalence of IA in suspected PTB remains unclear. During a period of 1 year (from January 2016 to December 2016), consecutive patients with suspected PTB were included in a referral TB hospital. Data, including demographic information and underlying diseases, were collected from medical records. PTB were all confirmed by mycobacterial culture (Lowenstein–Jensen medium). IA were diagnosed as proven or probable according to the criteria of the 2008 EORTC/MSG definitions. A descriptive analysis was performed to estimate the corresponding prevalence. During the study year, 1507 patients have a positive mycobacterial culture, with a mean age of 45.6 (s.d. 19.9) years old and a female:male ratio of 1:4. Among the 82 patients with non-tuberculous mycobacterial diseases, two patients (2.44%, 95% CI 0.67–8.46%) were diagnosed as IA (one proven and one probable); two probable IA patients (0.15%, 95% CI 0.04–0.55%) were diagnosed in PTB patients (n = 1315), and all were retreatment cases. In addition, all four IA patients (100%) exhibited cavities in both lobes on radiograph. In China, the prevalence of IA is low in active PTB patients. However, when high-risk factors for IA are encountered in PTB patients, further investigations are required and empirically treatment for IA might be warranted.

Vaccination has reduced the disease burden of vaccine-preventable diseases. However, the extent to which seasonal cycles of immunity could influence vaccine-induced immunity is not well understood. A national cross-sectional serosurveillance study performed in the Netherlands (Pienter-2) yielded data to investigate whether season of vaccination was associated with antibody responses induced by DT-IPV (diphtheria, tetanus and poliomyelitis), MMR (measles, mumps and rubella) and meningococcus C (MenC) vaccines in children. In total, 434 children met the inclusion criteria to study DT-IPV immunity, 811 for MMR and 311 for MenC. Differences in log(antibody levels) by season of vaccination were investigated with linear multivariable regression analyses. Seroconversion rates varied according to season of vaccination for rubella (90% of autumn-vaccinated children vs. 99% of winter-vaccinated had concentrations above cut-off levels). Summer-vaccinated boys showed a slower decline of tetanus antibodies (6% per month), in comparison with winter-vaccinated boys. In conclusion, season of vaccination showed little association with immunological protection. However, a number of associations were seen with a P-value of about 0.03; and adding data from a just-completed nationwide serological study might add more power to the current study. Further immunological and longitudinal investigations could help understand the mechanisms of seasonal influence in vaccine-induced responses.

The prevalence of Chagas disease has decreased in the Americas region due to vector control measures. However, non-vectorial transmission through blood transfusions and organ transplantation has gained importance in recent years. Screening among blood and organ donors are essential to reduce Trypanosoma cruzi transmission and could provide information to estimate population prevalence. We conducted a cross-sectional study on the prevalence of immunoglobulin G (IgG) antibodies against T. cruzi in healthy blood donors, solid organ donors and heart transplant recipients from 2012 to 2019. We found a total of 99 357 IgG T. cruzi results during the study period. The cumulative seroprevalence in healthy blood donors was 0.13% (95% confidence interval (CI) 0.10–0.15), in organ donors was 0.53% (95% CI 0.06–1.92) and in heart transplant recipients was 3.03 (95% CI 0.07–15.75). Seroprevalence trend in healthy blood donors showed annual increase between 2012 and 2015, decreasing in the following years. No trend was seen in organ donors neither heart recipients. Adjusted rates did not show difference by sex and age among blood donors. No significant increases in seroprevalence T. cruzi were found during the study period. T. cruzi transmission remains low.

A cluster of 18 scarlet fever cases and large illness absenteeism (32%, 58/184) in a school prompted concern and further investigation. We conducted telephone interviews with parents to ascertain cases and better comprehend parents' views. We identified 19 cases, of which 13 reported scarlet fever diagnosis by a physician and only seven fulfilled the probable case definition. We concluded that the outbreak was far smaller than suspected and found that communication and reporting could be improved. Accurate information and communication is essential in an outbreak; the school's concern could have been alleviated sooner and response measures better targeted.

The aim was to analyse invasive pneumococcal disease (IPD) serotypes in children aged ⩽17 years according to clinical presentation and antimicrobial susceptibility. We conducted a prospective study (January 2012–June 2016). IPD cases were diagnosed by culture and/or real-time polymerase chain reaction (PCR). Demographic, microbiological and clinical data were analysed. Associations were assessed using the odds ratio (OR) and 95% confidence intervals (CI). Of the 253 cases, 34.4% were aged <2 years, 38.7% 2–4 years and 26.9% 5–17 years. Over 64% were 13-valent pneumococcal conjugate vaccine (PCV13) serotypes. 48% of the cases were diagnosed only by real-time PCR. Serotypes 3 and 1 were associated with complicated pneumonia (P < 0.05) and non-PCV13 serotypes with meningitis (OR 7.32, 95% CI 2.33–22.99) and occult bacteraemia (OR 3.6, 95% CI 1.56–8.76). Serotype 19A was more frequent in children aged <2 years and serotypes 3 and 1 in children aged 2–4 years and 5–17 years, respectively. 36.1% of cases were not susceptible to penicillin and 16.4% were also non-susceptible to cefotaxime. Serotypes 14, 24F and 23B were associated with non-susceptibility to penicillin (P < 0.05) and serotypes 11, 14 and 19A to cefotaxime (P < 0.05). Serotype 19A showed resistance to penicillin (P = 0.002). In conclusion, PCV13 serotypes were most frequent in children aged ⩽17 years, mainly serotypes 3, 1 and 19A. Non-PCV13 serotypes were associated with meningitis and occult bacteraemia and PCV13 serotypes with pneumonia. Non-susceptibility to antibiotics of non-PCV13 serotypes should be monitored.

This study used hospital records from two time periods to understand the implication of COVID-19 on hospital-based deaths in Burundi. The place of COVID-19 symptoms was sought among deaths that occurred from January to May 2020 (during the pandemic) vs. January to May 2019 (before the pandemic). First, death proportions were tested to seize differences between mortality rates for each month in 2020 vs. 2019. In the second time, we compared mean time-to-death between the two periods using the Kaplan–Meier survival curve. Finally, a logistic regression was fitted to assess the likelihood of dying from COVID-19 symptoms between the two periods. We found statistical evidence of a higher death rate in May 2020 as compared to May 2019. Moreover, death occurred faster in 2020 (mean = 6.7 days, s.d. = 8.9) than in 2019 (mean = 7.8 days, s.d. = 10.9). Unlike in 2019, being a male was significantly associated with a much lower likelihood of dying with one or more COVID-19 symptom(s) in 2020 (odds ratio 0.35, 95% confidence interval 0.14–0.87). This study yielded some evidence for a possible COVID-19-related hospital-based mortality trend for May 2020. However, considering the time-constraint of the study, further similar studies over a longer period of time need to be conducted to trace a clearer picture on COVID-19 implication on hospital-based deaths in Burundi.