COVID-19 impacts population health equity. While mRNA vaccines protect against serious illness and death, little New Zealand (NZ) data exist about the impact of Omicron – and the effectiveness of vaccination – on different population groups. We aim to examine the impact of Omicron on Māori, Pacific, and Other ethnicities and how this interacts with age and vaccination status in the Te Manawa Taki Midland region of NZ. Daily COVID-19 infection and hospitalisation rates (1 February 2022 to 29 June 2022) were calculated for Māori, Pacific, and Other ethnicities for six age bands. A multivariate logistic regression model quantified the effects of ethnicity, age, and vaccination on hospitalisation rates. Per-capita Omicron cases were highest and occurred earliest among Pacific (9 per 1,000) and Māori (5 per 1,000) people and were highest among 12–24-year-olds (7 per 1,000). Hospitalisation was significantly more likely for Māori people (odds ratio (OR) = 2.03), Pacific people (OR = 1.75), over 75-year-olds (OR = 39.22), and unvaccinated people (OR = 4.64). Length of hospitalisation is strongly related to age. COVID-19 vaccination reduces hospitalisations for older individuals and Māori and Pacific populations. Omicron inequitably impacted Māori and Pacific people through higher per-capita infection and hospitalisation rates. Older people are more likely to be hospitalised and for longer.

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.

Burden of disease analyses can quantify the relative impact of different exposures on population health outcomes. Gastroenteritis where the causative pathogen was not determined and respiratory illness resulting from exposure to opportunistic pathogens transmitted by water aerosols have not always been considered in waterborne burden of disease estimates. We estimated the disease burden attributable to nine enteric pathogens, unspecified pathogens leading to gastroenteritis, and three opportunistic pathogens leading primarily to respiratory illness, in Ontario, Canada (population ~14 million). Employing a burden of disease framework, we attributed a fraction of annual (year 2016) emergency department (ED) visits, hospitalisations and deaths to waterborne transmission. Attributable fractions were developed from the literature and clinical input, and unattributed disease counts were obtained using administrative data. Our Monte Carlo simulation reflected uncertainty in the inputs. The estimated mean annual attributable rates for waterborne diseases were (per 100 000 population): 69 ED visits, 12 hospitalisations and 0.52 deaths. The corresponding 5th–95th percentile estimates were (per 100 000 population): 13–158 ED visits, 5–22 hospitalisations and 0.29–0.83 deaths. The burden of disease due to unspecified pathogens dominated these rates: 99% for ED visits, 63% for hospitalisations and 40% for deaths. However, when a causative pathogen was specified, the majority of hospitalisations (83%) and deaths (97%) resulted from exposure to the opportunistic pathogens Legionella spp., non-tuberculous mycobacteria and Pseudomonas spp. The waterborne disease burden in Ontario indicates the importance of gastroenteritis not traced back to a particular pathogen and of opportunistic pathogens transmitted primarily through contact with water aerosols.

We conducted probabilistic data linkage of three population datasets for the Northern Territory (NT), Australia, to describe the incidence of preterm births, stillbirths, low birthweight and small for gestational age (SGA) per 1000 NT births; and influenza and pertussis hospitalisations per 1 00 000 NT births in infants <7 months of age, in a pre-maternal vaccination era. The Perinatal Trends dataset (1994–2014) formed the cohort of 78 382 births. Aboriginal mother–infant pairs (37%) had disproportionately higher average annual rates (AR) for all adverse birth outcomes compared to their non-Aboriginal counterparts; rate ratios: preterm births 2.2 (AR 142.4 vs. 64.7); stillbirths 2.3 (AR 10.8 vs. 4.6); low birthweight 2.9 (AR 54 vs. 19); and SGA 1.7 (AR 187 vs. 111). Hospitalisation (2000–2015) and Immunisation Register datasets (1994–2015), showed that influenza hospitalisations (n = 53) and rates were 42.3 times higher in Aboriginal infants (AR 254 vs. 6); and that pertussis hospitalisations (n = 37) were 7.1 times higher in Aboriginal infants (AR 142.5 vs. 20.2) compared to non-Aboriginal infants. These baseline data are essential to assess the safety and effectiveness of influenza and pertussis vaccinations in pregnant women from the NT. Remote living Aboriginal women and infants stand to benefit the most from these vaccines.

Objective: To conduct a formative evaluation of a transitional intervention for family caregivers, with assessment of feasibility, acceptability, appropriateness, and potential benefits. Methods: The intervention aimed to provide emotional support, information on community resources, and information and support for development of coping skills for the caregivers of patients aged 65 and older who were to be discharged home from an acute medical hospital admission. We used a one-group, pre- and three-month post-test study design. Results: Ninety-one patient-caregiver dyads were recruited. Of these, 63 caregivers (69%) received all five planned intervention sessions, while 60 (66%) completed the post-test. There were significant reductions in caregiver anxiety and depression following the intervention, and high rates of satisfaction. Discussion: This transitional intervention should be further evaluated, preferably with a control group, either as a stand-alone intervention or as one component of a comprehensive transitional intervention for older patients and their caregivers.

Pneumonia is a leading cause of death in New York City (NYC). We identified spatial clusters of pneumonia-associated hospitalisation for persons residing in NYC, aged ⩾18 years during 2010–2014. We detected pneumonia-associated hospitalisations using an all-payer inpatient dataset. Using geostatistical semivariogram modelling, local Moran's I cluster analyses and χ2 tests, we characterised differences between ‘hot spots’ and ‘cold spots’ for pneumonia-associated hospitalisations. During 2010–2014, there were 141 730 pneumonia-associated hospitalisations across 188 NYC neighbourhoods, of which 43.5% (N = 61 712) were sub-classified as severe. Hot spots of pneumonia-associated hospitalisation spanned 26 neighbourhoods in the Bronx, Manhattan and Staten Island, whereas cold spots were found in lower Manhattan and northeastern Queens. We identified hot spots of severe pneumonia-associated hospitalisation in the northern Bronx and the northern tip of Staten Island. For severe pneumonia-associated hospitalisations, hot-spot patients were of lower mean age and a greater proportion identified as non-Hispanic Black compared with cold spot patients; additionally, hot-spot patients had a longer hospital stay and a greater proportion experienced in-hospital death compared with cold-spot patients. Pneumonia prevention efforts within NYC should consider examining the reasons for higher rates in hot-spot neighbourhoods, and focus interventions towards the Bronx, northern Manhattan and Staten Island.

The number of dengue epidemics in Brazil has increased dramatically in the last 15 years. In this study, we analysed the seasonal patterns in the incidence of hospitalisations due to dengue across the different states of Brazil and compared these with the corresponding climatic patterns. We discovered that the seasonality of dengue hospitalisations in Brazil has a clear zonal gradient, characterised by the progression of primary peaks from West to East during the first half of the year, which may be associated with the increased vapour pressure and rainfall during this period, leading to increased mosquito abundance and activity. We also found that the proportion of children among hospitalised individuals was especially high during the peak outbreaks in 2007/2008 and 2010. This may be due to the emergence and spread of the new DENV-2 Southeast Asian genotype lineage II from 2007, which has probably arrived from the Caribbean and may have caused an increase in incidence and severity of the disease, particularly among children. Our findings may allow health systems to improve control interventions and contribute to reducing dengue morbidity and mortality by using integrated vector control in conjunction with early diagnosis and prompt supportive care.