Despite considerable efforts to control tuberculosis (TB) among Ethiopian immigrants in Israel, an outbreak of TB among second-generation Ethiopian immigrants that involved native Israelis occurred between January 2011 and December 2019. The aim of this article is to report on this outbreak and discuss the patient and health system barriers that led to its propagation. Overall, 13 culture-positive TB patients were diagnosed in this outbreak. An additional 36 cases with identical mycobacterium tuberculosis genotypes were identified through cross-checking with the National TB Laboratory Registry. Among the 32 close contacts of the index case, 18 (56.3%) reported for screening and treatment of latent TB infection (LTBI) was recommended for 11 (61.1%) of them. However, none completed treatment and eight eventually developed TB. Of the 385 close contacts identified in this outbreak, 286 (74.3%) underwent contact investigation, 154 (53.8%) were recommended LTBI treatment, but only 26 (16.9%) completed the treatment. Routine contact investigation and treatment practice measures failed to contain the cascade of infection and disease, leading to the spread of the infecting strain of TB. This report highlights the challenges to identify the high-risk group and address barriers to care among such a vulnerable population.

The spread of COVID-19 is recent in India, which has within 4 months caused over 190 000 infections, as of 1 June 2020, despite four stringent lockdowns. With the current rate of the disease transmission in India, which is home to over 1.35 billion people, the infection spread is predicted to be worse than the USA in the upcoming months. To date, there is a major lack of understanding of the transmission dynamics and epidemiological characteristics of the disease in India, inhibiting effective measures to control the pandemic. We collected all the available data of the individual patients, cases and a range of parameters such as population distribution, testing and healthcare facilities, and weather, across all Indian states till May 2020. Numerical analysis was conducted to determine the effect of each parameter on the COVID-19 situation in India. A significant amount of local transmission in India initiated with travellers returning from abroad. Maharashtra, Tamil Nadu and Delhi are currently the top three infected states in India with doubling time of 14.5 days. The average recovery rate across Indian states is 42%, with a mortality rate below 3%. The rest 55% are currently active cases. In total, 88% of the patients experienced symptoms of high fever, 68% suffered from dry cough and 7.1% patients were asymptomatic. In total, 66.8% patients were males, 73% were in the age group of 20–59 years and over 83% recovered in 11–25 days. Approximately 3.4 million people were tested between 1 April and 25 May 2020, out of which 4% were detected COVID-19-positive. Given the current doubling time of infections, several states may face a major shortage of public beds and healthcare facilities soon. Weather has minimal effect on the infection spread in most Indian states. The study results will help policymakers to predict the trends of the disease spread in the upcoming months and devise better control measures.

Diagnostic testing for the novel coronavirus is an important tool to fight the coronavirus disease (Covid-19) pandemic. However, testing capacities are limited. A modified testing protocol, whereby a number of probes are ‘pooled’ (i.e. grouped), is known to increase the capacity for testing. Here, we model pooled testing with a double-average model, which we think to be close to reality for Covid-19 testing. The optimal pool size and the effect of test errors are considered. The results show that the best pool size is three to five, under reasonable assumptions. Pool testing even reduces the number of false positives in the absence of dilution effects.

Purpose: The novel coronavirus (severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)) first appeared in Wuhan, China, in December 2019, and rapidly spread across the globe. Since most respiratory viruses are known to show a seasonal pattern of infection, it has been hypothesised that SARS-CoV-2 may be seasonally dependent as well. The present study looks at a possible effect of atmospheric temperature, which is one of the suspected factors influencing seasonality, on the evolution of the pandemic. Basic procedures: Since confirming a seasonal pattern would take several more months of observation, we conducted an innovative day-to-day micro-correlation analysis of nine outbreak locations, across four continents and both hemispheres, in order to examine a possible relationship between atmospheric temperature (used as a proxy for seasonality) and outbreak progression. Main findings: There was a negative correlation between atmospheric temperature variations and daily new cases growth rates, in all nine outbreaks, with a median lag of 10 days. Principal conclusions: The results presented here suggest that high temperatures might dampen SARS-CoV-2 propagation, while lower temperatures might increase its transmission. Our hypothesis is that this could support a potential effect of atmospheric temperature on coronavirus disease progression, and potentially a seasonal pattern for this virus, with a peak in the cold season and rarer occurrences in the summer. This could guide government policy in both the Northern and Southern hemispheres for the months to come.

During the last months and following the implementation of containment measures in the context of coronavirus disease 2019 (COVID-19) pandemic, the number of new human immunodeficiency virus (HIV) diagnoses radically decreased in Liege AIDS Reference Center, Belgium. The number of HIV screening tests has also dramatically dropped down to an unprecedented level. This decline of HIV diagnosis is caused by missed diagnoses of individuals infected before the establishment of such measures and to the reduction of high-risk sexual behaviours during the COVID-19 pandemic.

In mainland China, the clinical, epidemiological and genetic features of non-O1/non-O139 Vibrio cholerae (NOVC) bacteraemia have been scarcely investigated. Herein, we describe a patient with NOVC bacteraemia diagnosed in our hospital and present a retrospective analysis of literature reports of 32 other cases in China, detailing the clinical epidemiology, antibiotic resistance and molecular characteristics of isolates. Most patients were male (84.8%; median age, 53 years) and had predisposing factors, such as cirrhosis, malignant tumours, blood diseases and diabetes. In addition to fever, gastroenteritis was the most frequent presenting symptom. The mortality rate during hospitalisation was 12.1%. NOVC bacteraemia cases were more common in June–August, with the majority in coastal provinces and the Yangtze River basin. Only 42.4% of cases were attributed to consumption of marine (aquatic) products. Tetracycline, third-generation cephalosporins, and fluoroquinolones were the most effective antimicrobial agents, and the highest frequencies of resistance were recorded for ampicillin/sulbactam (37.5%), amoxicillin/clavulanic acid (33.3%), ampicillin (29.2%) and sulfamethoxazole (20%). Multi-drug resistant isolates were not detected. Limited data indicate that ctxAB and tcpA genes were absent in all NOVC isolates but other putative virulence genes (hlyA, toxR, hap and rtxA) were common. Ten multilocus sequence types were identified with marked genetic heterogeneity between different isolates. As clinical manifestations of NOVC bacteraemia may vary widely, and isolates exhibit genetic diversity, clinicians and public health experts should be alerted to the possibility of infection with this pathogen because of the high prevalence of liver disease in China.

Surveillance of new cases of invasive pneumococcal disease (IPD) in Italy was started in 2007 by the Ministry of Health (MoH). In 2012, pneumococcal childhood vaccination was introduced at the national level and, in 2017, for citizens aged 65 years and over. We describe here IPD epidemiology in Italy over the past 10 years investigating the impact of the vaccine programme on disease burden. Reports of IPD cases, data on serotype and vaccination coverage (VC) data were obtained from MoH annual reports, for the period 2007–2017. IPD notification rate and proportion by year, region, age and serotype were calculated. In 2007, 525 cases were reported (rate 0.88/100 000), rising to 1703 cases (rate 2.82/100 000) in 2017. The distribution of IPD cases by age group over time registered the largest share among individuals aged 65 years and over. A decreasing trend in notification rate was observed among those aged 0–4 years. During the same period, the 24-month VC increased, ranging from 80.9% to 96.7% in 2017. Molecular data indicated re-emergence of PPSV23-specific serotypes and non-vaccine serotypes. We observed an increase in IPD notifications during 2007–2017, likely due to an improved surveillance system, at least in some regions, with the relative quota of IPD notifications decreasing among vaccinated children cohorts. Further strengthening of IPD surveillance system, including molecular and vaccine coverage data, would be needed to assess and inform pneumococcal vaccination strategies in Italy.

This study aimed to analyse the trend and spatial–temporal clusters of risk of transmission of COVID-19 in northeastern Brazil. We conducted an ecological study using spatial and temporal trend analysis. All confirmed cases of COVID-19 in the Northeast region of Brazil were included, from 7 March to 22 May 2020. We used the segmented log-linear regression model to assess time trends, and the local empirical Bayesian estimator, the global and local Moran indexes for spatial analysis. The prospective space–time scan statistic was performed using the Poisson probability distribution model. There were 113 951 confirmed cases of COVID-19. The average incidence rate was 199.73 cases/100 000 inhabitants. We observed an increasing trend in the incidence rate in all states. Spatial autocorrelation was reported in metropolitan areas, and 178 municipalities were considered a priority, especially in the states of Ceará and Maranhão. We identified 11 spatiotemporal clusters of COVID-19 cases; the primary cluster included 70 municipalities from Ceará state. COVID-19 epidemic is increasing rapidly throughout the Northeast region of Brazil, with dispersion towards countryside. It was identified high risk clusters for COVID-19, especially in the coastal side.

Despite SARS-CoV-19 infection has a stereotypical clinical picture, isolated cases with unusual manifestations have been reported, some of them being well-known to be triggered by viral infections. However, the real frequency in COVID-19 is unknown. Analysing data of 63 822 COVID patients attending 50 Spanish emergency department (ED) during the COVID outbreak, before hospitalisation, we report frequencies of (myo)pericarditis (0.71‰), meningoencephalitis (0.25‰), Guillain–Barré syndrome (0.13‰), acute pancreatitis (0.71‰) and spontaneous pneumothorax (0.57‰). Compared with general ED population, COVID patients developed more frequently Guillain–Barré syndrome (odds ratio (OR) 4.55, 95% confidence interval (CI) 2.09–9.90), spontaneous pneumothorax (OR 1.98, 95% CI 1.40–2.79) and (myo)pericarditis (OR 1.45, 95% CI 1.07–1.97), but less frequently pancreatitis (OR 0.44, 95% CI 0.33–0.60).

The aim of this study was to apply a back-calculation model to Great Britain (GB) classical scrapie surveillance data, and use this model to estimate how many more cases might be expected, and over what time frame these cases might occur. A back-calculation model was applied to scrapie surveillance data between 2005 and 2019 to estimate the annual rate of decline of classical scrapie. This rate was then extrapolated to predict the number of future cases each year going forward. The model shows that there may be yet further cases of classical scrapie in GB. These will most likely occur in the fallen stock scheme, with approximately a 25% probability of at least 1 further scrapie positive, with a very low probability (~0.2%) of having up to three additional scrapie positives. This highlights the difficulty of completely eliminating all further cases, even in the presence of very effective control measures.

Klebsiella pneumoniae is a common pathogen associated with nosocomial infections and is characterised serologically by capsular polysaccharide (K) and lipopolysaccharide O antigens. We surveyed a total of 348 non-duplicate K. pneumoniae clinical isolates collected over a 1-year period in a tertiary care hospital, and determined their O and K serotypes by sequencing of the wbb Y and wzi gene loci, respectively. Isolates were also screened for antimicrobial resistance and hypervirulent phenotypes; 94 (27.0%) were identified as carbapenem-resistant (CRKP) and 110 (31.6%) as hypervirulent (hvKP). isolates fell into 58 K, and six O types, with 92.0% and 94.2% typeability, respectively. The predominant K types were K14K64 (16.38%), K1 (14.66%), K2 (8.05%) and K57 (5.46%), while O1 (46%), O2a (27.9%) and O3 (11.8%) were the most common. CRKP and hvKP strains had different serotype distributions with O2a:K14K64 (41.0%) being the most frequent among CRKP, and O1:K1 (26.4%) and O1:K2 (17.3%) among hvKP strains. Serotyping by gene sequencing proved to be a useful tool to inform the clinical epidemiology of K. pneumoniae infections and provides valuable data relevant to vaccine design.

Given the fast spread of the novel coronavirus (COVID-19) worldwide and its classification by the World Health Organization (WHO) as being one of the worst pandemics in history, several scientific studies are carried out using various statistical and mathematical models to predict and study the likely evolution of this pandemic in the world. In the present research paper, we present a brief study aiming to predict the probability of reaching a new record number of COVID-19 cases in Lebanon, based on the record theory, giving more insights about the rate of its quick spread in Lebanon. The main advantage of the records theory resides in avoiding several statistical constraints concerning the choice of the underlying distribution and the quality of the residuals. In addition, this theory could be used, in cases where the number of available observations is somehow small. Moreover, this theory offers an alternative solution in case where machine learning techniques and long-term memory models are inapplicable because they need a considerable amount of data to be performant. The originality of this paper lies in presenting a new statistical approach allowing the early detection of unexpected phenomena such as the new pandemic COVID-19. For this purpose, we used epidemiological data from Johns Hopkins University to predict the trend of COVID-2019 in Lebanon. Our method is useful in calculating the probability of reaching a new record as well as studying the propagation of the disease. It also computes the probabilities of the waiting time to observe the future COVID-19 record. Our results obviously confirm the quick spread of the disease in Lebanon over a short time.

Acute haemorrhagic conjunctivitis is a highly contagious eye disease, the prediction of acute haemorrhagic conjunctivitis is very important to prevent and grasp its development trend. We use the exponential smoothing model and the seasonal autoregressive integrated moving average (SARIMA) model to analyse and predict. The monthly incidence data from 2004 to 2017 were used to fit two models, the actual incidence of acute haemorrhagic conjunctivitis in 2018 was used to validate the model. Finally, the prediction effect of exponential smoothing is best, the mean square error and the mean absolute percentage error were 0.0152 and 0.1871, respectively. In addition, the incidence of acute haemorrhagic conjunctivitis in Chongqing had a seasonal trend characteristic, with the peak period from June to September each year.

We report key learning from the public health management of the first two confirmed cases of COVID-19 identified in the UK. The first case imported, and the second associated with probable person-to-person transmission within the UK. Contact tracing was complex and fast-moving. Potential exposures for both cases were reviewed, and 52 contacts were identified. No further confirmed COVID-19 cases have been linked epidemiologically to these two cases. As steps are made to enhance contact tracing across the UK, the lessons learned from earlier contact tracing during the country's containment phase are particularly important and timely.

We recruited 1591 patients who presented to our fever clinics from 23 January 2020 to 16 February 2020. The different imaging findings between COVID-19 pneumonia and influenza A viruses, influenza B virus pneumonia were also investigated. Most patients were infected by influenza A and B viruses in the flu-season. A laboratory kit is urgently needed to test different viruses simultaneously. Computed tomography can help early screen suspected patients with COVID-19 and differentiate different virus-related pneumonia.

During the coronavirus disease 2019 (COVID-19) pandemic, a new phenomenon manifesting as a multisystem inflammatory syndrome in children (MIS-C) which has a similar clinical presentation to Kawasaki disease, toxic shock syndrome and severe sepsis has emerged. Although the number of MIS-C reports is increasing, rare reports in Asia is still available. To our knowledge, this study is the largest series of published MIS-C cases in Iran. We performed a retrospective study of all patients with case definition for MIS-C admitted to the three paediatric hospitals in Iran. All of these hospitals are located within the most active COVID-19 pandemic areas (Tehran, Qom and Mazandaran) in Iran. Demographic characteristics, clinical data, laboratory findings, imaging and echocardiographic findings, treatment and outcomes were collected. Between 7 March and 23 June 2020, 45 children were included in the study. The median age of children was 7 years (range between 10 months and 17 years). Common presenting symptoms include fever (91%), abdominal pain (58%), nausea/vomiting (51%), mucocutaneous rash (53%), conjunctivitis (51%) and hands and feet oedema (40%) with median duration of symptoms prior to presentation of 5 (interquartile range (IQR) 3, 7) days. Fifty-three percent of children showed lymphopaenia. Overall, the majority of cases at admission had markedly elevated inflammatory markers erythrocyte sedimentation rate (ESR) (95.5%) and C-reactive protein (CRP) (97%). Ferritin was abnormal in 11 out of 14 tested patients (73%), and it was highly elevated (>500 ng/ml) in 47% of cases. Median fibrinogen level was 210 (IQR 165, 291) mg/dl, D-dimer was 3909 (IQR 848, 4528) ng/ml and troponin was 0.6 (IQR 0.1, 26) ng/ml, respectively. Twenty out of 31 patients (64.5%) had hypoalbuminaemia. In addition, hyponatraemia was found in 64% of cases. Twenty-five patients (56%) presented with cardiac involvement and acute renal failure was observed in 13 cases (29%). Pleural, ascitic, ileitis and pericardial effusions were found in 18%, 11%, 4% and 2% of cases, respectively. In conclusion, this is a first large case series of hospitalised children who met criteria for MIS-C in Iran. There was a wide spectrum of presenting signs and symptoms; evidence of inflammation with abnormal values of CRP, ESR, D-dimer, ferritin and albumin; and multi-organ involvement.

This study estimates the incubation period of COVID-19 among locally transmitted cases, and its association with age to better inform public health measures in containing COVID-19. Epidemiological data of all PCR-confirmed COVID-19 cases from all restructured hospitals in Singapore were collected between 23 January 2020 and 2 April 2020. Activity mapping and detailed epidemiological investigation were conducted by trained personnel. Positive cases without clear exposure to another positive case were excluded from the analysis. One hundred and sixty-four cases (15.6% of patients) met the inclusion criteria during the defined period. The crude median incubation period was 5 days (range 1–12 days) and median age was 42 years (range 5–79 years). The median incubation period among those 70 years and older was significantly longer than those younger than 70 years (8 vis-à-vis 5 days, P = 0.040). Incubation period was negatively correlated with day of illness in both groups. These findings support current policies of 14-day quarantine periods for close contacts of confirmed cases and 28 days for monitoring infections in known clusters. An elderly person who may have a longer incubation period than a younger counterpart may benefit from earlier and proactive testing, especially after exposure to a positive case.

This study aimed to analyse the survival of patients admitted to Brazilian hospitals due to the COVID-19 and estimate prognostic factors. This is a retrospective, multicentre cohort study, based on data from 46 285 hospitalisations for COVID-19 in Brazil. Survival functions were calculated using the Kaplan–Meier's method. The log-rank test compared the survival functions for each variable and from that, hazard ratios (HRs) were calculated, and the proportional hazard model was used in Cox multiple regression. The smallest survival curves were the ones for patients at the age of 68 years or more, black/mixed race, illiterate, living in the countryside, dyspnoea, respiratory distress, influenza-like outbreak, O2 saturation <95%, X-ray change, length of stay in the intensive care unit (ICU), invasive ventilatory support, previous heart disease, pneumopathy, diabetes, Down's syndrome, neurological disease and kidney disease. Better survival was observed in the influenza-like outbreak and in an asthmatic patient. The multiple model for increased risk of death when they were admitted to the ICU HR 1.28, diabetes HR 1.17, neurological disease HR 1.34, kidney disease HR 1.11, heart disease HR 1.14, black or mixed race of HR 1.50, asthma HR 0.71 and pneumopathy HR 1.12. This reinforces the importance of socio-demographic and clinical factors as a prognosis for death.

We aimed to describe the clinical features in coronavirus disease 2019 (COVID-19) cases. We studied 134 critically ill COVID-19 cases from 30 December 2019 to 20 February 2020 in an intensive care unit (ICU) at Wuhan Jinyintan Hospital. Demographics, underlying diseases, therapy strategies and test results were collected and analysed from patients on admission, admission to the ICU and 48 h before death. The non-survivors were older (65.46 (s.d. 9.74) vs. 46.45 (s.d. 11.09)) and were more likely to have underlying diseases. The blood group distribution of the COVID-19 cases differed from that of the Han population in Wuhan, with type A being 43.85%; type B, 26.92%; type AB, 10% and type O, 19.23%. Non-survivors tend to develop more severe lymphopaenia, with higher C-reactive protein, interleukin-6, procalcitonin, D-dimer levels and gradually increased with time. The clinical manifestations were non-specific. Compared with survivors, non-survivors more likely to have organ function injury, and to receive mechanical ventilation, either invasively or noninvasively. Multiple organ failure and secondary bacterial infection in the later period is worthy of attention.

India is one of the severely affected countries by the Covid-19 pandemic at present. Within the stochastic framework of the SEQIR model, we studied publicly available data of the Covid-19 patients in India and analysed possible impacts of quarantine and social distancing as controlling strategies for the pandemic. Our stochastic simulation results clearly show that proper quarantine and social distancing should be maintained right from the start of the pandemic and continued until its end for effective control. This calls for a more disciplined social lifestyle in the future. However, only social distancing and quarantine of the exposed population are found not sufficient enough to end the pandemic in India. Therefore, implementation of other stringent policies like complete lockdown as well as increased testing of susceptible populations is necessary. The demographic stochasticity, which is quite visible in the system dynamics, has a critical role in regulating and controlling the pandemic.