Weight calibration in the joint modelling of medical cost and mortality.

Joint modelling of longitudinal and time-to-event data is a method that recognizes the dependency between the two data types, and combines the two outcomes into a single model, which leads to more precise estimates. These models are applicable when individuals are followed over a period of time, generally to monitor the progression of a disease or a medical condition, and also when longitudinal covariates are available. Medical cost datasets are often also available in longitudinal scenarios, but these datasets usually arise from a complex sampling design rather than simple random sampling and such complex sampling design needs to be accounted for in the statistical analysis. Ignoring the sampling mechanism can lead to misleading conclusions. This article proposes a novel approach to the joint modelling of complex data by combining survey calibration with standard joint modelling. This is achieved by incorporating a new set of equations to calibrate the sampling weights for the survival model in a joint model setting. The proposed method is applied to data on anti-dementia medication costs and mortality in people with diagnosed dementia in New Zealand.

Falls Risk in Long-Term Care Residents With Cognitive Impairment: Effects of COVID-19 Pandemic.

OBJECTIVES: The aim of this study was to investigate the impact of the COVID-19 pandemic on falls rates in long-term care residents with cognitive impairment. DESIGN: An observational study using routinely collected national interRAI data. SETTING AND PARTICIPANTS: Participants were from long-term care residents (age ≥60 years) who received an interRAI Long Term Care Facility assessment anywhere in New Zealand between August 17, 2018, and August 16, 2022. METHODS: The primary outcome was "At least 1 fall in the last 30 days." Based on the Cognitive Performance Scale (CPS), cognitive impairment was categorized into 3 levels: intact or borderline intact (0-1), mild to moderate impairment (2-3), and moderately to very severe impairment (4-6). The COVID-19 pandemic was divided into 3 periods (First wave: March 21, 2020, to June 8, 2020; Varying level of community outbreaks: June 9, 2020 to August 16, 2021; and Delta-Omicron wave: August 17, 2021, to August 16, 2021) and compared to a pre-COVID-19 period (August 17, 2018, to March 20, 2020). Cox regression modeling was used to study falls and interactions between CPS and COVID-19 pandemic periods, along with other established falls risk factors in the literature. RESULTS: A total of 282,518 interRAI-LTCF assessments from 75,132 unique residents were included. Interactions between CPS and COVID-19 pandemic periods found that cognitive impairment was associated with a higher hazard ratio (ranged from 1.22 to 1.37) in each of the 3 COVID-19 pandemic periods. We also found unstable health, unsteady gait, wandering, and moderate to severe ADL dependency were the strongest risk factors for falls. CONCLUSIONS AND IMPLICATIONS: Cognitively impaired long-term care residents had an increased risk for falls during the COVID-19 pandemic. This risk was influenced by several factors. In future pandemic or infection control related isolation, residents who are most at risk can be identified for targeted falls prevention programs.

Exploring older peoples' attitudes and preferences around the use of their healthcare information.

AIMS: Routinely collected health data can provide rich information for research and epidemiological monitoring of different diseases, but using the data presents many challenges. This study aims to explore the attitudes and preferences of people aged 55 and over regarding the use of their de-identified health data, and their concerns and comfort in different scenarios. METHODS: An anonymous online survey was conducted with people aged 55 and over currently engaged with health services in a New Zealand health district during June-October 2022. The survey could be completed online or by telephone and was available in eight languages. RESULTS: Seventy-nine percent of respondents knew that their health information was currently being used in the ways described in the scenarios, and between 80-87% felt comfortable or very comfortable with their data being used as described in the scenarios. In contrast, 4% (n=9) felt "uncomfortable" or "very uncomfortable" across all of the scenarios. Participants expressed concerns about data accuracy, privacy and confidentiality, security, transparency of use, consent, feedback and the risk of data being sold to commercial companies. Some participants identified situations where permission should be required to link data, including being used by people other than health professionals, containing sensitive health issues, or being used for commercial purposes. CONCLUSION: This study finds general support from patients for the use of their routinely collected data for secondary purposes as long as its use will benefit the population from which the data are taken. It also highlights the necessity of including the perspectives of different cultures in the collection, storage, use and analysis of health information, particularly concerning Maori cultural considerations.

Identifying potential patients with diabetes-related dementia: a descriptive approach using routinely collected data.

AIMS: Diabetes-related dementia (DRD) is a new dementia subtype associated with type 2 diabetes mellitus, first described in 2013. This study investigated data from a local New Zealand memory service to identify patients that met the criteria for DRD. METHODS: Using routinely collected data from 2013-2021, we selected a sample of people with dementia, diabetes, and no CT evidence of Alzheimer's disease (AD), vascular dementia, or frontotemporal dementia. We compared their socio-demographic, clinical, and cognitive characteristics with a sample of patients with diabetes and Alzheimer's disease. RESULTS: Forty (16%) of 249 patients with diabetes and dementia had "normal" CT scans (DRD subgroup), and 38 (15%) had AD (AD subgroup). Compared to NZ Europeans, disproportionally more Maori and Pacific Islanders (70.2%) were in the DRD subgroup. In the Pacific subgroup (n=31), the DRD subgroup had higher memory subscores than the AD subgroup (p=0.047), and the Kaplan-Meier plot suggested poorer survival (p=0.13). Maori patients with diabetes and dementia were more likely to meet all four criteria for DRD. CONCLUSION: We have replicated the findings of the 2013 DRD research and have demonstrated a higher risk for the DRD subtype of dementia among the Maori and Pacific Islander patients in our sample.

Living with Dementia in Aotearoa (LiDiA): A Feasibility Study for a Dementia Prevalence Study in Maori and Non-Maori Living in New Zealand.

INTRODUCTION: Recent estimations have projected a threefold increase in dementia prevalence in Aotearoa New Zealand (NZ) by 2050, particularly in Maori and Pacific peoples. However, to date, there are no national data on dementia prevalence, and overseas data are used to estimate the NZ dementia statistics. The aim of this feasibility study was to prepare the groundwork for the first full-scale NZ dementia prevalence study that is representative of Maori, European, Pacific and Asian peoples living in NZ. METHODS: The main feasibility issues were: (i) Sampling to ensure adequate community representation from the included ethnic groups, (ii) Preparing a workforce to conduct the fieldwork and developing quality control, (iii) Raising awareness of the study in the communities (iv) Maximizing recruitment by door-knocking, (v) Retaining those we have recruited to the study and (vi) Acceptability of study recruitment and assessment using adapted versions of the 10/66 dementia protocol in different ethnic groups living in South Auckland. RESULTS: We found that a probability sampling strategy using NZ Census data was reasonably accurate and all ethnic groups were sampled effectively. We demonstrated that we were able to train up a multi-ethnic workforce consisting of lay interviewers who were able to administer the 10/66 dementia protocol in community settings. The response rate (224/297, 75.5%) at the door-knocking stage was good but attrition at subsequent stages was high and only 75/297 (25.2%) received the full interview. CONCLUSIONS: Our study showed that it would be feasible to conduct a population-based dementia prevalence study using the 10/66 dementia protocol in Maori, European and Asian communities living in NZ, utilizing a qualified, skilled research team representative of the families participating in the study. The study has demonstrated that for recruitment and interviewing in Pacific communities a different but culturally appropriate approach is required.

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.

Anti-dementia medication use in Aotearoa New Zealand: An exploratory study using health data from the Integrated Data Infrastructure (IDI).

OBJECTIVE: Anti-dementia medications such as acetylcholinesterase inhibitors are an important part of the management pathway for dementia. However, there are limited data in New Zealand that have examined the rates and patterns of use of funded anti-dementia medication and how use differs with ethnicity, age and sex. METHODS: This was a retrospective population-based descriptive study. Using the Integrated Data Infrastructure, we identified individuals of all ages coded for a diagnosis of dementia and estimated the proportion dispensed funded anti-dementia medication - donepezil tablets and rivastigmine patches - between 1 July 2016 and 30 June 2020. Rates of medication use in five main ethnic groups (Maori, Pacific peoples, Asian, European, and Middle Eastern, Latin American and African) in the <65, 65-79 and 80 and over (80+) age groups were compared and also between males and females in all sub-groups. Log-binomial models were used to calculate relative risks to determine any differences in anti-dementia medication use in the five ethnic groups and the three age groups and between males and females in each of the four study years. RESULTS: Overall, one-third of the dementia population received a funded anti-dementia medication in the total population (all ages) between 2016 and 2020. Donepezil tablets were dispensed in 31.6-34.0% and rivastigmine patches in 1.4-2.1% across the four study years. Compared to people of European ethnicity, Maori, Pacific peoples, and Middle Eastern, Latin American and African groups were less likely to be dispensed an anti-dementia medication (Maori: relative risk = 0.79-0.81, p < 0.0001; Pacific peoples: relative risk = 0.72-0.74, p < 0.0001; Middle Eastern, Latin American and African: relative risk = 0.73-0.78, p < 0.05). Compared to the age 80+ group, the 65-79 age group was more likely (relative risk = 1.50-1.54, p < 0.0001), while the age <65 group was less likely (relative risk = 0.67-0.71, p < 0.0001) to be dispensed an anti-dementia medication. There were no statistically significant differences in anti-dementia medication use between males and females. CONCLUSION: This study provides important information about funded anti-dementia medication use in New Zealand and how this differs by ethnicity, age and sex. Despite higher dementia prevalence in Maori and Pacific peoples, these groups were less likely to receive funded anti-dementia medication.

Optimal sampling allocation for outcome-dependent designs in cluster-correlated data settings.

In clinical and public health studies, it is often the case that some variables relevant to the analysis are too difficult or costly to measure for all individuals in the population of interest. Rather, a subsample of these individuals must be identified for additional data collection. A sampling scheme that incorporates readily-available information for the entire target population at the design stage can increase the statistical efficiency of the intended analysis. While there is no universally optimal sampling design, under certain principles and restrictions, a well-designed and efficient sampling strategy can be implemented. In two-phase designs, efficiency can be gained by stratifying on the outcome and/or auxiliary information that is known at phase I. Additional gains in efficiency can be obtained by determining the optimal allocation of the sample sizes across the strata, which depends on the quantity that is being estimated. In this paper, the inference is concerned with one or multiple regression parameter(s) where the study units are naturally clustered and, thus, exhibit correlation in outcomes. We propose several allocation strategies within the framework of two-phase designs for the estimation of the regression parameter(s) obtained from weighted generalized estimating equations. The proposed methods extend existing theory to address the objective of the estimating regression parameters in cluster-correlated data settings by minimizing the asymptotic variance of the estimator subject to a fixed sample size. Through a comprehensive simulation study, we show that the proposed allocation schemes have the potential to yield substantial efficiency gains over alternative strategies.

Indigenous adolescent health in Aotearoa New Zealand: Trends, policy and advancing equity for rangatahi Maori, 2001-2019.

Background: Rangatahi Maori, the Indigenous adolescents of Aotearoa New Zealand (NZ), have poorer health outcomes than Pakeha (NZ European /other European/"White") adolescents. We explored the influence of policies for Indigenous youth by presenting health trends, inequities and contrasting policy case examples: tobacco control and healthcare access. Methods: Cross-sectional representative surveys of NZ secondary school students were undertaken in 2001, 2007, 2012 and 2019. Health indicators are presented for Maori and Pakeha adolescents (relative risks with 95% CI, calculated using modified Poisson regression) between 2001-2019 and 2012-2019. Policy examples were examined utilising Critical Te Tiriti Analysis (CTA). Findings: Rangatahi Maori reported significant health gains between 2001 and 2019, but an increase in depressive symptoms (13.8% in 2012 to 27.9% in 2019, RR 2.01 [1.65-2.46]). Compared to Pakeha youth there was a pattern of persistent Maori disadvantage, particularly for racism (RR 2.27 [2.08-2.47]), depressive symptoms (RR 1.42 [1.27-1.59]) and forgone healthcare (RR 1.63 [1.45-1.84]). Tobacco use inequities narrowed (RR 2.53 [2.12-3.02] in 2007 to RR 1.55 [1.25-1.93] in 2019). CTA reveals rangatahi Maori-specific policies, Maori leadership, and political support aligned with improved outcomes and narrowing inequities. Interpretation: Age-appropriate Indigenous strategies are required to improve health outcomes and reduce inequities for rangatahi Maori. Characteristics of effective strategies include: (1) evidence-based, sustained, and comprehensive approaches including both universal levers and Indigenous youth-specific policies; (2) Indigenous and rangatahi leadership; (3) the political will to address Indigenous youth rights, preferences, priorities; and (4) a commitment to an anti-racist praxis and healthcare Indigenisation. Funding: Two Health Research Council of New Zealand Project Grants: (a) Fleming T, Peiris-John R, Crengle S, Parry D. (2018). Integrating survey and intervention research for youth health gains. (HRC ref: 18/473); and (b) Clark TC, Le Grice J, Groot S, Shepherd M, Lewycka S. (2017) Harnessing the spark of life: Maximising whanau contributors to rangatahi wellbeing (HRC ref: 17/315).

Prevalence of young-onset dementia: nationwide analysis of routinely collected data.

INTRODUCTION: Young-onset dementia prevalence is understudied internationally. Previous studies have been limited by low case numbers, reliance on single sources of routinely collected health data for case identification and inclusion of a limited age range. Our objective was to determine the 1-year period prevalence of diagnosed dementia in people aged 0-64 in the entire New Zealand population using routinely collected health data. METHODS: A population-based descriptive study was carried out in New Zealand (population 4.8 million) using routinely collected deidentified health data from 2016 to 2020. Dementia cases in seven linked health datasets in the New Zealand Integrated Data Infrastructure were identified using diagnostic codes and/or use of antidementia medication. Prevalence for each of the four study years was calculated by age, sex and ethnicity. RESULTS: From a total population of 4 027 332-4 169 754 individuals aged 0-64, we identified 3396-3474 cases of 'all-cause' dementia in each of the study years (prevalence crude range: 83-84/100 000 people aged 0-64; 139-141/100 000 people aged 30-64 years; 204-207/100 000 people aged 45-64 years). Age-standardised prevalence was higher in males than females. Age-standardised and sex-standardised prevalence was higher in Maori and Pacific People than European and Asian. DISCUSSION: By using a large study population and multiple national health datasets, we have minimised selection bias and estimated the national prevalence of diagnosed young-onset dementia with precision. Young-onset dementia prevalence for the total New Zealand population was similar to reported global prevalence, validating previous estimates. Prevalence differed by ethnicity, which has important implications for service planning.

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.

Small-sample inference for cluster-based outcome-dependent sampling schemes in resource-limited settings: Investigating low birthweight in Rwanda.

The neonatal mortality rate in Rwanda remains above the United Nations Sustainable Development Goal 3 target of 12 deaths per 1000 live births. As part of a larger effort to reduce preventable neonatal deaths in the country, we conducted a study to examine risk factors for low birthweight. The data were collected via a cost-efficient cluster-based outcome-dependent sampling (ODS) scheme wherein clusters of individuals (health centers) were selected on the basis of, in part, the outcome rate of the individuals. For a given data set collected via a cluster-based ODS scheme, estimation for a marginal model may proceed via inverse-probability-weighted generalized estimating equations, where the cluster-specific weights are the inverse probability of the health center's inclusion in the sample. In this paper, we provide a detailed treatment of the asymptotic properties of this estimator, together with an explicit expression for the asymptotic variance and a corresponding estimator. Furthermore, motivated by the study we conducted in Rwanda, we propose a number of small-sample bias corrections to both the point estimates and the standard error estimates. Through simulation, we show that applying these corrections when the number of clusters is small generally reduces the bias in the point estimates, and results in closer to nominal coverage. The proposed methods are applied to data from 18 health centers and 1 district hospital in Rwanda.

Dementia prevalence estimation among the main ethnic groups in New Zealand: a population-based descriptive study of routinely collected health data.

OBJECTIVE: Estimates of dementia prevalence in New Zealand (NZ) have previously been extrapolated from limited Australasian studies, which may be neither accurate nor reflect NZ's unique population and diverse ethnic groups. This study used routinely collected health data to estimate the 1-year period prevalence for diagnosed dementia for each of the 4 years between July 2016 and June 2020 in the age 60+ and age 80+ populations and for the four main ethnic groups. DESIGN: A population-based descriptive study. SETTING: Seven national health data sets within the NZ Integrated Data Infrastructure (IDI) were linked. Diagnosed dementia prevalence for each year was calculated using the IDI age 60+ and age 80+ populations as the denominator and also age-sex standardised to allow comparison across ethnic groups. PARTICIPANTS: Diagnosed dementia individuals in the health datasets were identified by diagnostic or medication codes used in each of the data sets with deduplication of those who appeared in more than one data set. RESULTS: The crude diagnosed dementia prevalence was 3.8%-4.0% in the age 60+ population and 13.7%-14.4% in the age 80+ population across the four study years. Dementia prevalence age-sex standardised to the IDI population in the last study period of 2019-2020 was 5.4% for Maori, 6.3% for Pacific Islander, 3.7% for European and 3.4% for Asian in the age 60+ population, and 17.5% for Maori, 22.2% for Pacific Islander, 13.6% for European and 13.5% for Asian in the age 80+ population. CONCLUSIONS: This study provides the best estimate to date for dementia prevalence in NZ but is limited to those people who were identified as having dementia based on data from the seven included data sets. The findings suggest that diagnosed dementia prevalence is higher in Maori and Pacific Islanders. A nationwide NZ community-based dementia prevalence study is much needed to confirm the findings of this study.

Sociodemographic and Clinical Characteristics of 1350 Patients With Young Onset Dementia: A Comparison With Older Patients.

OBJECTIVE: To determine the sociodemographic and clinical characteristics of a large cohort of patients with young onset dementia (YOD) (aged below 65), and whether they differ from older (age 65+) adults with dementia. METHODS: Retrospective cross-sectional study. Participants were New Zealanders who were assessed with International Residential Assessment Instrument (interRAI) assessments (including community-dwelling adults and those in long-term care) from 2016 to 2019 and had a diagnosis of dementia. Outcomes were sociodemographic and clinical characteristics captured in the interRAI assessment. RESULTS: People with YOD were more likely to be male, of non-European ethnicity, and live in a dwelling other than a private home or be homeless. They were more likely to exhibit problematic behaviors and neuropsychiatric symptoms but were less frail and less dependent for activities of daily living. Financial strain and loneliness were more common in people with YOD. Carers of people with YOD were more likely to feel distress, anger, or depression, and families of people with YOD were more likely to feel overwhelmed. CONCLUSIONS: YOD patients have different needs than older adults with dementia. These differences must be considered by clinicians and organizations that provide care and support to people living with dementia.

Diagnostic Accuracy of 10/66 Dementia Protocol in Fijian-Indian Elders Living in New Zealand.

The 10/66 dementia protocol was developed as a language and culture-fair instrument to estimate the prevalence of dementia in non-English speaking communities. The aim of this study was to validate the 10/66 dementia protocol in elders of Indian ethnicity born in the Fiji Islands (Fijian-Indian) living in New Zealand. To our knowledge, this is the first time a dementia diagnostic tool has been evaluated in the Fijian-Indian population in New Zealand. We translated and adapted the 10/66 dementia protocol for use in in Fijian-Indian people. Individuals (age ≥ 65) who self-identified as Fijian-Indian and had either been assessed for dementia at a local memory service (13 cases, eight controls) or had participated in a concurrent dementia prevalence feasibility study (eight controls) participated. The sensitivity, specificity, positive predictive value, and Youden's index were obtained by comparing the 10/66 diagnosis and its sub-components against the clinical diagnosis (reference standard). The 10/66 diagnosis had a sensitivity of 92.3% (95% CI 70.3-99.5), specificity of 93.8% (95% CI 75.3-99.6), positive predictive value of 92.3% (95% CI 70.3-99.5), and negative predictive value of 93.8% (95% CI 75.3-99.6). The study results show that the Fijian-Indian 10/66 dementia protocol has adequate discriminatory abilities to diagnose dementia in our sample. This instrument would be suitable for future dementia population-based studies in the Fijian-Indian population living in Aotearoa/New Zealand or the Fiji-Islands.

Living with Dementia in Aotearoa (LiDiA): a cross-sectional feasibility study protocol for a multiethnic dementia prevalence study in Aotearoa/New Zealand.

INTRODUCTION: Aotearoa/New Zealand (NZ) is officially recognised as a bicultural country composed of Maori and non-Maori. Recent estimations have projected a threefold increase in dementia prevalence in NZ by 2050, with the greatest increase in non-NZ-Europeans. The NZ government will need to develop policies and plan services to meet the demands of the rapid rise in dementia cases. However, to date, there are no national data on dementia prevalence and overseas data are used to estimate the NZ dementia statistics. The overall aim of the Living with Dementia in Aotearoa study was to prepare the groundwork for a large full-scale NZ dementia prevalence study. METHODS AND ANALYSIS: The study has two phases. In phase I, we will adapt and translate the 10/66 dementia assessment protocol to be administered in Maori, Samoan, Tongan and Fijian-Indian elders. The diagnostic accuracy of the adapted 10/66 protocol will be tested in older people from these ethnic backgrounds who were assessed for dementia at a local memory service. In phase II, we will address the feasibility issues of conducting a population-based prevalence study by applying the adapted 10/66 protocol in South Auckland and will include NZ-European, Maori, Samoan, Tongan, Chinese and Fijian-Indian participants. The feasibility issues to be explored are as follows: (1) how do we sample to ensure we get accurate community representation? (2) how do we prepare a workforce to conduct the fieldwork and develop quality control? (3) how do we raise awareness of the study in the community to maximise recruitment? (4) how do we conduct door knocking to maximise recruitment? (5) how do we retain those we have recruited to remain in the study? (6) what is the acceptability of study recruitment and the 10/66 assessment process in different ethnic groups? ETHICS AND DISSEMINATION: The validity and feasibility studies were approved by the New Zealand Northern A Health and Disability Ethics Committee (numbers 17NTA234 and 18NTA176, respectively). The findings will be disseminated through peer-reviewed academic journals, national and international conferences, and public events. Data will be available on reasonable request from the corresponding author.

Using Big Data to Estimate Dementia Prevalence in New Zealand: Protocol for an Observational Study.

BACKGROUND: Dementia describes a cluster of symptoms that includes memory loss; difficulties with thinking, problem solving, or language; and functional impairment. Dementia can be caused by a number of neurodegenerative diseases, such as Alzheimer disease and cerebrovascular disease. Currently in New Zealand, most of the systematically collected and detailed information on dementia is obtained through a suite of International Residential Assessment Instrument (interRAI) assessments, including the home care, contact assessment, and long-term care facility versions. These versions of interRAI are standardized comprehensive geriatric assessments. Patients are referred to have an interRAI assessment by the Needs Assessment and Service Coordination (NASC) services after a series of screening processes. Previous estimates of the prevalence and costs of dementia in New Zealand have been based on international studies with different populations and health and social care systems. This new local knowledge will have implications for estimating the demographic distribution and socioeconomic impact of dementia in New Zealand. OBJECTIVE: This study investigates the prevalence of dementia, risk factors for dementia, and drivers of the informal cost of dementia among people registered in the NASC database in New Zealand. METHODS: This study aims to analyze secondary data routinely collected by the NASC and interRAI (home care and contact assessment versions) databases between July 1, 2014, and July 1, 2019, in New Zealand. The databases will be linked to produce an integrated data set, which will be used to (1) investigate the sociodemographic and clinical risk factors associated with dementia and other neurological conditions, (2) estimate the prevalence of dementia using weighting methods for complex samples, and (3) identify the cost of informal care per client (in number of hours of care provided by unpaid carers) and the drivers of such costs. We will use design-based survey methods for the estimation of prevalence and generalized estimating equations for regression models and correlated and longitudinal data. RESULTS: The results will provide much needed statistics regarding dementia prevalence and risk factors and the cost of informal care for people living with dementia in New Zealand. Potential health inequities for different ethnic groups will be highlighted, which can then be used by decision makers to inform the development of policy and practice. CONCLUSIONS: As of November 2020, there were no dementia prevalence studies or studies on informal care costs of dementia using national data from New Zealand. All existing studies have used data from other populations with substantially different demographic distributions. This study will give insight into the actual prevalence, risk factors, and informal care costs of dementia for the population with support needs in New Zealand. It will provide valuable information to improve health outcomes and better inform policy and planning. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/20225.

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.

Augmented pseudo-likelihood estimation for two-phase studies.

In many public health and medical research settings, information on key covariates may not be readily available or too expensive to gather for all individuals in the study. In such settings, the two-phase design provides a way forward by first stratifying an initial (large) phase I sample on the basis of covariates readily available (including, possibly, the outcome), and sub-sampling participants at phase II to collect the expensive measure(s). When the outcome of interest is binary, several methods have been proposed for estimation and inference for the parameters of a logistic regression model, including weighted likelihood, pseudo-likelihood and maximum likelihood. Although these methods yield consistent estimation and valid inference, they do so solely on the basis of the phase I stratification and the detailed covariate information obtained at phase II. Moreover, they ignore any additional information that is readily available at phase I but was not used as part of the stratified sampling design. Motivated by the potential for efficiency gains, especially concerning parameters corresponding to the additional phase I covariates, we propose a novel augmented pseudo-likelihood estimator for two-phase studies that makes use of all available information. In contrast to recently-proposed weighted likelihood-based methods that calibrate to the influence function of the model of interest, the methods we propose do not require the development of additional models and, therefore, enjoy a degree of robustness. In addition, we expand the broader framework for pseudo-likelihood based estimation and inference to permit link functions for binary regression other than the logit link. Comprehensive simulations, based on a one-time cross sectional survey of 82,887 patients undergoing anti-retroviral therapy in Malawi between 2005 and 2007, illustrate finite sample properties of the proposed methods and compare their performance competing approaches. The proposed method yields the lowest standard errors when the model is correctly specified. Finally, the methods are applied to a large implementation science project examining the effect of an enhanced community health worker program to improve adherence to WHO guidelines for at least four antenatal visits, in Dar es Salaam, Tanzania.