Recent studies have provided insights into the pathogenesis of coronavirus disease 2019 (COVID-19) 1 – 4 . However, the longitudinal immunological correlates of disease outcome remain unclear. Here we serially analysed immune responses in 113 patients with moderate or severe COVID-19. Immune profiling revealed an overall increase in innate cell lineages, with a concomitant reduction in T cell number. An early elevation in cytokine levels was associated with worse disease outcomes. Following an early increase in cytokines, patients with moderate COVID-19 displayed a progressive reduction in type 1 (antiviral) and type 3 (antifungal) responses. By contrast, patients with severe COVID-19 maintained these elevated responses throughout the course of the disease. Moreover, severe COVID-19 was accompanied by an increase in multiple type 2 (anti-helminths) effectors, including interleukin-5 (IL-5), IL-13, immunoglobulin E and eosinophils. Unsupervised clustering analysis identified four immune signatures, representing growth factors (A), type-2/3 cytokines (B), mixed type-1/2/3 cytokines (C), and chemokines (D) that correlated with three distinct disease trajectories. The immune profiles of patients who recovered from moderate COVID-19 were enriched in tissue reparative growth factor signature A, whereas the profiles of those with who developed severe disease had elevated levels of all four signatures. Thus, we have identified a maladapted immune response profile associated with severe COVID-19 and poor clinical outcome, as well as early immune signatures that correlate with divergent disease trajectories.

BackgroundLeptospirosis, a spirochaetal zoonosis, occurs in diverse epidemiological settings and affects vulnerable populations, such as rural subsistence farmers and urban slum dwellers. Although leptospirosis is a life-threatening disease and recognized as an important cause of pulmonary haemorrhage syndrome, the lack of global estimates for morbidity and mortality has contributed to its neglected disease status.Methodology/Principal FindingsWe conducted a systematic review of published morbidity and mortality studies and databases to extract information on disease incidence and case fatality ratios. Linear regression and Monte Carlo modelling were used to obtain age and gender-adjusted estimates of disease morbidity for countries and Global Burden of Disease (GBD) and WHO regions. We estimated mortality using models that incorporated age and gender-adjusted disease morbidity and case fatality ratios. The review identified 80 studies on disease incidence from 34 countries that met quality criteria. In certain regions, such as Africa, few quality assured studies were identified. The regression model, which incorporated country-specific variables of population structure, life expectancy at birth, distance from the equator, tropical island, and urbanization, accounted for a significant proportion (R2 = 0.60) of the variation in observed disease incidence. We estimate that there were annually 1.03 million cases (95% CI 434,000–1,750,000) and 58,900 deaths (95% CI 23,800–95,900) due to leptospirosis worldwide. A large proportion of cases (48%, 95% CI 40–61%) and deaths (42%, 95% CI 34–53%) were estimated to occur in adult males with age of 20–49 years. Highest estimates of disease morbidity and mortality were observed in GBD regions of South and Southeast Asia, Oceania, Caribbean, Andean, Central, and Tropical Latin America, and East Sub-Saharan Africa.Conclusions/SignificanceLeptospirosis is among the leading zoonotic causes of morbidity worldwide and accounts for numbers of deaths, which approach or exceed those for other causes of haemorrhagic fever. Highest morbidity and mortality were estimated to occur in resource-poor countries, which include regions where the burden of leptospirosis has been underappreciated.

CLIA-certified laboratories were enrolled through the IMPACT biorepository study 15. In the IMPACT study, biospecimens including blood, nasopharyngeal swabs, saliva, urine and stool samples were collected at study enrolment (baseline denotes the first time point) and longitudinally on average every 3 to 7 days (serial time points). The detailed demographics and clinical characteristics of these 98 participants are shown in Extended Data Table 1. Plasma and peripheral blood mononuclear cells (PBMCs) were isolated from whole blood, and plasma was used for titre measurements of SARS-CoV-2 spike S1 protein-specific IgG and IgM antibodies (anti-S1-IgG and-IgM) and cytokine or chemokine measurements. Freshly isolated PBMCs were stained and analysed by flow cytometry 15. We obtained longitudinal serial time-point samples from a subset of these 98 study participants (n = 48; information in Extended Data Table 1). To compare the immune phenotypes between sexes, two sets of data analyses were performed in parallel-baseline and longitudinal, as described below. As a control group, healthcare workers (HCWs) from Yale-New Haven Hospital were enrolled who were uninfected with COVID-19. Demographics and background information for the HCW group and the demographics of HCWs for cytokine assays and flow cytometry assays for the primary analyses are in Extended Data Table 1. Demographic data, time-point information of the samples defined by the days from the symptom onset (DFSO) in each patient, treatment information, and raw data used to generate figures and tables is in Supplementary Table 1. Baseline analysis The baseline analysis was performed on samples from the first time point of patients who met the following criteria: not in intensive care unit (ICU), had not received tocilizumab, and had not received high doses of corticosteroids (prednisone equivalent of more than 40 mg) before the first sample collection date. This patient group, cohort A, consisted of 39 patients (17 male and 22 female) (Extended Data Tables 1, 2). Intersex and transgender individuals were not represented in this study. Figures 1-4 represent analyses of baseline raw values obtained from patients in cohort A. In cohort A patients, male and female patients were matched in terms of age, body mass index (BMI), and DFSO at the first time point sample collection (Extended Data Fig. 1a). However, there were significant differences in age and BMI between HCW controls and patients (patients had higher age and BMI values) (Extended Data Table 1), and therefore an age-and BMI-adjusted difference-indifferences analysis was also performed in parallel (Extended Data Table 3). Longitudinal analysis As parallel secondary analyses, we performed longitudinal analysis on a total patient cohort (cohort B) to evaluate the difference in immune response over the course of the disease between male and female patients. Cohort B included all patient samples from cohort A (including several time-point samples from the cohort A patients) as well as an additional 59 patients who d...

Leptospirosis is a zoonotic disease which has emerged as a major cause of morbidity and mortality among impoverished populations. One centenary after the discovery of the causative spirochaetal agent, little is understood of Leptospira pathogenesis, which in turn has hampered the identification of new intervention strategies to address this neglected disease. However the recent availability of complete genome sequences for Leptospira and discovery of genetic tools to transform the pathogen has led to major insights into the biology and pathogenesis of this pathogen. We discuss the life cycle of the bacterium and the new advances that have been made and their implications for the future prevention of this disease.

We measured severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in primary sewage sludge in the New Haven, Connecticut, USA, metropolitan area during the Coronavirus Disease 2019 (COVID-19) outbreak in Spring 2020. SARS-CoV-2 RNA was detected throughout the more than 10-week study and, when adjusted for time lags, tracked the rise and fall of cases seen in SARS-CoV-2 clinical test results and local COVID-19 hospital admissions. Relative to these indicators, SARS-CoV-2 RNA concentrations in sludge were 0-2 d ahead of SARS-CoV-2 positive test results by date of specimen collection, 0-2 d ahead of the percentage of positive tests by date of specimen collection, 1-4 d ahead of local hospital admissions and 6-8 d ahead of SARS-CoV-2 positive test results by reporting date. Our data show the utility of viral RNA monitoring in municipal wastewater for SARS-CoV-2 infection surveillance at a population-wide level. In communities facing a delay between specimen collection and the reporting of test results, immediate wastewater results can provide considerable advance notice of infection dynamics. The progression of the COVID-19 pandemic has been monitored primarily by testing symptomatic individuals for the presence of SARS-CoV-2 RNA and counting the number of positive tests over time 1. However, in the United States and other countries, the spread of COVID-19 has commonly exceeded the testing capacity of public health systems. Moreover, test results are a lagging indicator of the pandemic's progression 2,3 , because testing is usually prompted by symptoms, which might take 2 weeks to present after infection 4 , and delays occur between the appearance of symptoms, testing and the reporting of test results. Monitoring sewage in a community's collection or treatment system has been used previously to provide early surveillance of disease prevalence at a population-wide level, notably for polio 5,6 , and might be similarly beneficial for the current COVID-19 pandemic. SARS-CoV-2 RNA is present in the stool of patients with COVID-19 (refs. 7-9) and in raw wastewater 10-12 , and increased RNA concentrations in raw wastewater have been recently associated with increases in reported COVID-19 cases 11. However, the utility of wastewater SARS-CoV-2 concentrations for tracking the progression of COVID-19 infections is poorly understood. In this study, we investigated how viral RNA concentrations in

Zoonotic spillover, which is the transmission of a pathogen from a vertebrate animal to a human, presents a global public health burden but is a poorly understood phenomenon. Zoonotic spillover requires several factors to align, including the ecological, epidemiological and behavioural determinants of pathogen exposure, and the within-human factors that affect susceptibility to infection. In this Opinion article, we propose a synthetic framework for animal-to-human transmission that integrates the relevant mechanisms. This framework reveals that all zoonotic pathogens must overcome a hierarchical series of barriers to cause spillover infections in humans. Understanding how these barriers are functionally and quantitatively linked, and how they interact in space and time, will substantially improve our ability to predict or prevent spillover events. This work provides a foundation for transdisciplinary investigation of spillover and synthetic theory on zoonotic transmission.

Major progress has been made in the basic research of leptospirosis. Future challenges will be to translate these advances into public health measures for developing countries. Yet the most effective responses may be interventions that directly address the determinants of poverty, such as poor sanitation, which are often responsible for transmission.

The informal settlements of the Global South are the least prepared for the pandemic of COVID-19 since basic needs such as water, toilets, sewers, drainage, waste collection, and secure and adequate housing are already in short supply or non-existent. Further, space constraints, violence, and overcrowding in slums make physical distancing and self-quarantine impractical, and the rapid spread of an infection highly likely. J Urban Health international aid, NGOs, and community groups to innovate beyond disaster response and move toward longterm plans.