Impacts of the COVID-19 lockdown on self-reported mood and self-rated health of community-dwelling adults with chronic illness.

AIM: To determine whether self-reported mood or self-rated health were affected in community-dwelling adults with chronic illness following COVID-19 lockdown. METHODS: This was a repeated cross-sectional study using secondary data. We included New Zealanders aged 40+ who underwent International Residential Instrument (interRAI) assessments in the year prior to COVID-19 lockdown (25 March 2019-24 March 2020) or in the year following COVID-19 lockdown (25 March 2020-24 March 2021). Pairwise comparisons were made between each pre-lockdown quarter and its respective post-lockdown quarter to account for seasonality patterns. Data from 45,553 (pre-lockdown) and 45,349 (post-lockdown) assessments were analysed. Outcomes (self-reported mood, self-rated health) were stratified by socio-demographic variables. RESULTS: Self-reported mood improved in the first quarter post-lockdown among those aged 80+, as well as among women, people of European ethnicity, those living alone and those living in more deprived areas. Self-rated health improved in these same groups, as well as among those aged 65-79, and among men. No differences in self-reported mood or self-rated health were found in the second, third, or fourth quarters post-lockdown. CONCLUSIONS: Self-reported mood and self-rated health of community-dwelling adults with chronic illness were not negatively affected following COVID-19 lockdown, and temporarily improved among some sub-groups. However, the longer-term impacts of the COVID-19 pandemic need to be closely monitored.

Impact of the first wave of COVID-19 on the health and psychosocial well-being of Maori, Pacific Peoples and New Zealand Europeans living in aged residential care.

OBJECTIVE: To investigate the impact of New Zealand's (NZ) first wave of COVID-19, which included a nationwide lockdown, on the health and psychosocial well-being of Maori, Pacific Peoples and NZ Europeans in aged residential care (ARC). METHODS: interRAI assessments of Maori, Pacific Peoples and NZ Europeans (aged 60 years and older) completed between 21/3/2020 and 8/6/2020 were compared with assessments of the same ethnicities during the same period in the previous year (21/3/2019 to 8/6/2019). Physical, cognitive, psychosocial and service utilisation indicators were included in the bivariate analyses. RESULTS: A total of 538 Maori, 276 Pacific Peoples and 11,322 NZ Europeans had an interRAI assessment during the first wave of COVID-19, while there were 549 Maori, 248 Pacific Peoples and 12,367 NZ Europeans in the comparative period. Fewer Maori reported feeling lonely (7.8% vs. 4.5%, p = 0.021), but more NZ Europeans reported severe depressive symptoms (6.9% vs. 6.3%, p = 0.028) during COVID-19. Lower rates of hospitalisation were observed in Maori (7.4% vs. 10.9%, p = 0.046) and NZ Europeans (8.1% vs. 9.4%, p < 0.001) during COVID-19. CONCLUSIONS: We found a lower rate of loneliness in Maori but a higher rate of depression in NZ European ARC populations during the first wave of COVID-19. Further research, including qualitative studies with ARC staff, residents and families, and different ethnic communities, is needed to explain these ethnic group differences. Longer-term effects from the COVID-19 pandemic on ARC populations should also be investigated.

Predicting Hospital Demand During the COVID-19 Outbreak in Bogotá, Colombia.

Colombia, like many developing nations, does not have a strong health system able to respond to a pandemic of the magnitude of Covid-19. There is an increasing need to create a model that allows particular clinics and hospitals to estimate the number of patients that require Intensive Care Units-ICU care (critical), and the number of patients that require hospital care (severe), but not ICU care, in order to manage their limited resources. This paper presents a prediction of the total number of ICU and regular beds that will be needed in Bogotá, Colombia, during the COVID-19 pandemic. We use an SEIR model that includes three different categories of infection: those who can stay at home, those who need regular hospital beds, and those who need ICU treatment. The model allows for a time varying transmission rate which we use to incorporate the measures introduced by the government over the period of one semester. The model predicts that by mid November 2020, the city will need 1362 ICU beds and more than 9000 regular hospital beds. The number of active cases will be 67,866 by then and the death toll will reach 13,268 people by the end of December. We provide a Shiny app available at https://claudia-rivera-rodriguez.shinyapps.io/shinyappcovidclinic/. The original values in the app reproduce the results of this paper, but the parameters and starting values can be changed according to the user's needs. COVID-19 has posed too many challenges to health systems around the globe. This model is a useful tool for cities, hospitals and clinics in Colombia that need to be prepared for the excess demand of services that a pandemic like this one generates. Unfortunately, the model predicts that by mid-November the projected capacity of the system in Bogotá will not be enough. We expect the lockdown rules to be strengthened in future days, so the death toll will not be as bad as predicted by this model.

Impact of COVID-19 on the health and psychosocial status of vulnerable older adults: study protocol for an observational study.

BACKGROUND: Many countries around the world have adopted social distancing as one of the public health measures to reduce COVID-19 transmissions in the community. Such measures could have negative effects on the mental health of the population. The aims of this study are to (1) track the impact of COVID-19 on self-reported mood, self-rated health, other health and psychosocial indicators, and health services utilization of people who have an interRAI assessment during the first year of COVID-19; (2) compare these indicators with the same indicators in people who had an interRAI assessment in the year before COVID-19; and (3) report these indicators publicly as soon as data analysis is completed every 3 months. METHODS: interRAI COVID-19 Study (iCoS) is an observational study on routinely collected national data using the interRAI Home Care and Contact Assessment, which are standardized geriatric assessment tools mandated for all people assessed for publicly funded home support services and aged residential care in New Zealand. Based on the 2018/19 figures, we estimated there are 36,000 interRAI assessments per annum. We will compare the four post-lockdown quarters (from 25th March 2020) with the respective pre-lockdown quarters. The primary outcomes are self-reported mood (feeling sad, depressed or hopeless: 0 = no, 1 = yes) and self-rated health (0 = excellent, 1 = good, 2 = fair, 3 = poor). We will also analyze sociodemographics, other secondary health and psychosocial indicators, and health services utilization. Descriptive statistics will be conducted for primary outcomes and other indicators for each of the eight quarters. We will compare the quarters using regression models adjusted for demographic characteristics using weights or additional variables. Key health and psychosocial indicators will be reported publicly as soon as data analysis is completed for each quarter in the 12-month post-lockdown period by using a data visualization tool. DISCUSSION: This rapid translation of routinely collected national interRAI data will provide a means to monitor the health and psychosocial well-being of vulnerable older New Zealanders. Insights from this study can be shared with other countries that use interRAI and prepare health and social services for similar epidemics/pandemics in the future.