Novel multimorbidity clusters in people with eczema and asthma:a population-based cluster analysis

Eczema and asthma are allergic diseases and two of the commonest chronic conditions in high-income countries. Their co-existence with other allergic conditions is common, but little research exists on wider multimorbidity with these conditions. We set out to identify and compare clusters of multimorbidity in people with eczema or asthma and people without. Using routinely-collected primary care data from the U.K. Clinical Research Practice Datalink GOLD, we identified adults ever having eczema (or asthma), and comparison groups never having eczema (or asthma). We derived clusters of multimorbidity from hierarchical cluster analysis of Jaccard distances between pairs of diagnostic categories estimated from mixed-effects logistic regressions. We analysed 434,422 individuals with eczema (58% female, median age 47 years) and 1,333,281 individuals without (55% female, 47 years), and 517,712 individuals with asthma (53% female, 44 years) and 1,601,210 individuals without (53% female, 45 years). Age at first morbidity, sex and having eczema/asthma affected the scope of multimorbidity, with women, older age and eczema/asthma being associated with larger morbidity clusters. Injuries, digestive, nervous system and mental health disorders were more commonly seen in eczema and asthma than control clusters. People with eczema and asthma of all ages and both sexes may experience greater multimorbidity than people without eczema and asthma, including conditions not previously recognised as contributing to their disease burden. This work highlights areas where there is a critical need for research addressing the burden and drivers of multimorbidity in order to inform strategies to reduce poor health outcomes

Using paired serology and surveillance data to quantify dengue transmission and control during a large outbreak in Fiji.

Dengue is a major health burden, but it can be challenging to examine transmission and evaluate control measures because outbreaks depend on multiple factors, including human population structure, prior immunity and climate. We combined population-representative paired sera collected before and after the 2013/14 dengue-3 outbreak in Fiji with surveillance data to determine how such factors influence transmission and control in island settings. Our results suggested the 10-19 year-old age group had the highest risk of infection, but we did not find strong evidence that other demographic or environmental risk factors were linked to seroconversion. A mathematical model jointly fitted to surveillance and serological data suggested that herd immunity and seasonally varying transmission could not explain observed dynamics. However, the model showed evidence of an additional reduction in transmission coinciding with a vector clean-up campaign, which may have contributed to the decline in cases in the later stages of the outbreak

Novel multimorbidity clusters in people with eczema and asthma: a population-based cluster analysis.

Eczema and asthma are allergic diseases and two of the commonest chronic conditions in high-income countries. Their co-existence with other allergic conditions is common, but little research exists on wider multimorbidity with these conditions. We set out to identify and compare clusters of multimorbidity in people with eczema or asthma and people without. Using routinely-collected primary care data from the U.K. Clinical Research Practice Datalink GOLD, we identified adults ever having eczema (or asthma), and comparison groups never having eczema (or asthma). We derived clusters of multimorbidity from hierarchical cluster analysis of Jaccard distances between pairs of diagnostic categories estimated from mixed-effects logistic regressions. We analysed 434,422 individuals with eczema (58% female, median age 47 years) and 1,333,281 individuals without (55% female, 47 years), and 517,712 individuals with asthma (53% female, 44 years) and 1,601,210 individuals without (53% female, 45 years). Age at first morbidity, sex and having eczema/asthma affected the scope of multimorbidity, with women, older age and eczema/asthma being associated with larger morbidity clusters. Injuries, digestive, nervous system and mental health disorders were more commonly seen in eczema and asthma than control clusters. People with eczema and asthma of all ages and both sexes may experience greater multimorbidity than people without eczema and asthma, including conditions not previously recognised as contributing to their disease burden. This work highlights areas where there is a critical need for research addressing the burden and drivers of multimorbidity in order to inform strategies to reduce poor health outcomes

Ethnic differences in the indirect effects of the COVID-19 pandemic on clinical monitoring and hospitalisations for non-COVID conditions in England: a population-based, observational cohort study using the OpenSAFELY platform

Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. // Methods: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. // Findings: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. // Interpretation: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes

Healthcare utilisation in people with long COVID: an OpenSAFELY cohort study.

BACKGROUND: Long COVID potentially increases healthcare utilisation and costs. However, its impact on the NHS remains to be determined. METHODS: This study aims to assess the healthcare utilisation of individuals with long COVID. With the approval of NHS England, we conducted a matched cohort study using primary and secondary care data via OpenSAFELY, a platform for analysing anonymous electronic health records. The long COVID exposure group, defined by diagnostic codes, was matched with five comparators without long COVID between Nov 2020 and Jan 2023. We compared their total healthcare utilisation from GP consultations, prescriptions, hospital admissions, A&E visits, and outpatient appointments. Healthcare utilisation and costs were evaluated using a two-part model adjusting for covariates. Using a difference-in-difference model, we also compared healthcare utilisation after long COVID with pre-pandemic records. RESULTS: We identified 52,988 individuals with a long COVID diagnosis, matched to 264,867 comparators without a diagnosis. In the 12 months post-diagnosis, there was strong evidence that those with long COVID were more likely to use healthcare resources (OR: 8.29, 95% CI: 7.74-8.87), and have 49% more healthcare utilisation (RR: 1.49, 95% CI: 1.48-1.51). Our model estimated that the long COVID group had 30 healthcare visits per year (predicted mean: 29.23, 95% CI: 28.58-29.92), compared to 16 in the comparator group (predicted mean visits: 16.04, 95% CI: 15.73-16.36). Individuals with long COVID were more likely to have non-zero healthcare expenditures (OR = 7.66, 95% CI = 7.20-8.15), with costs being 44% higher than the comparator group (cost ratio = 1.44, 95% CI: 1.39-1.50). The long COVID group costs approximately £2500 per person per year (predicted mean cost: £2562.50, 95% CI: £2335.60-£2819.22), and the comparator group costs £1500 (predicted mean cost: £1527.43, 95% CI: £1404.33-1664.45). Historically, individuals with long COVID utilised healthcare resources more frequently, but their average healthcare utilisation increased more after being diagnosed with long COVID, compared to the comparator group. CONCLUSIONS: Long COVID increases healthcare utilisation and costs. Public health policies should allocate more resources towards preventing, treating, and supporting individuals with long COVID

Interactions between timing and transmissibility explain diverse flavivirus dynamics in Fiji.

Zika virus (ZIKV) has caused large, brief outbreaks in isolated populations, however ZIKV can also persist at low levels over multiple years. The reasons for these diverse transmission dynamics remain poorly understood. In Fiji, which has experienced multiple large single-season dengue epidemics, there was evidence of multi-year transmission of ZIKV between 2013 and 2017. To identify factors that could explain these differences in dynamics between closely related mosquito-borne flaviviruses, we jointly fit a transmission dynamic model to surveillance, serological and molecular data. We estimate that the observed dynamics of ZIKV were the result of two key factors: strong seasonal effects, which created an ecologically optimal time of year for outbreaks; and introduction of ZIKV after this optimal time, which allowed ZIKV transmission to persist over multiple seasons. The ability to jointly fit to multiple data sources could help identify a similar range of possible outbreak dynamics in other settings

COVID-19 collateral: Indirect acute effects of the pandemic on physical and mental health in the UK

ABSTRACTBackgroundConcerns have been raised that the response to the UK COVID-19 pandemic may have worsened physical and mental health, and reduced use of health services. However, the scale of the problem is unquantified, impeding development of effective mitigations. We asked what has happened to general practice contacts for acute physical and mental health outcomes during the pandemic?MethodsUsing electronic health records from the Clinical Research Practice Datalink (CPRD) Aurum (2017-2020), we calculated weekly primary care contacts for selected acute physical and mental health conditions (including: anxiety, depression, acute alcohol-related events, asthma and chronic obstructive pulmonary disease [COPD] exacerbations, cardiovascular and diabetic emergencies). We used interrupted time series (ITS) analysis to formally quantify changes in conditions after the introduction of population-wide restrictions (‘lockdown’) compared to the period prior to their introduction in March 2020.FindingsThe overall population included 9,863,903 individuals on 1st January 2017. Primary care contacts for all conditions dropped dramatically after introduction of population-wide restrictions. By July 2020, except for unstable angina and acute alcohol-related events, contacts for all conditions had not recovered to pre-lockdown levels. The largest reductions were for contacts for: diabetic emergencies (OR: 0.35, 95% CI: 0.25-0.50), depression (OR: 0.53, 95% CI: 0.52-0.53), and self-harm (OR: 0.56, 95% CI: 0.54-0.58).InterpretationThere were substantial reductions in primary care contacts for acute physical and mental conditions with restrictions, with limited recovery by July 2020. It is likely that much of the deficit in care represents unmet need, with implications for subsequent morbidity and premature mortality. The conditions we studied are sufficiently severe that any unmet need will have substantial ramifications for the people experiencing the conditions and healthcare provision. Maintaining access must be a key priority in future public health planning (including further restrictions).FundingWellcome Trust Senior Fellowship (SML), Health Data Research UK.RESULTS IN CONTEXTEvidence before this studyA small study in 47 GP practices in a largely deprived, urban area of the UK (Salford) reported that primary care consultations for four broad diagnostic groups (circulatory disease, common mental health problems, type 2 diabetes mellitus and malignant cancer) declined by 16-50% between March and May 2020, compared to what was expected based on data from January 2010 to March 2020. We searched Medline for other relevant evidence of the indirect effect of the COVID-19 pandemic on physical and mental health from inception to September 25th 2020, for articles published in English, with titles including the search terms (“covid*” or “coronavirus” or “sars-cov-2”), and title or abstracts including the search terms (“indirect impact” or “missed diagnos*” or “missing diagnos*” or “delayed diagnos*” or ((“present*” or “consult*” or “engag*” or “access*”) AND (“reduction” or “decrease” or “decline”)). We found no further studies investigating the change in primary care contacts for specific physical- and mental-health conditions indirectly resulting from the COVID-19 pandemic or its control measures. There has been a reduction in hospital admissions and presentations to accident and emergency departments in the UK, particularly for myocardial infarctions and cerebrovascular accidents. However, there is no published evidence specifically investigating the changes in primary care contacts for severe acute physical and mental health conditions.Added value of this studyTo our knowledge this is the first study to explore changes in healthcare contacts for acute physical and mental health conditions in a large population representative of the UK. We used electronic primary care health records of nearly 10 million individuals across the UK to investigate the indirect impact of COVID-19 on primary care contacts for mental health, acute alcohol-related events, asthma/chronic obstructive pulmonary disease (COPD) exacerbations, and cardiovascular and diabetic emergencies up to July 2020. For all conditions studied, we found primary care contacts dropped dramatically following the introduction of population-wide restriction measures in March 2020. By July 2020, with the exception of unstable angina and acute alcohol-related events, primary care contacts for all conditions studied had not recovered to pre-lockdown levels. In the general population, estimates of the absolute reduction in the number of primary care contacts up to July 2020, compared to what we would expect from previous years varied from fewer than 10 contacts per million for some cardiovascular outcomes, to 12,800 per million for depression and 6,600 for anxiety. In people with COPD, we estimated there were 43,900 per million fewer contacts for COPD exacerbations up to July 2020 than what we would expect from previous years.Implicatins of all the available evidenceWhile our results may represent some genuine reduction in disease frequency (e.g. the restriction measures may have improved diabetic glycaemic control due to more regular daily routines at home), it is more likely the reduced primary care conatcts we saw represent a substantial burden of unmet need (particularly for mental health conditions) that may be reflected in subsequent increased mortality and morbidity. Health service providers should take steps to prepare for increased demand in the coming months and years due to the short and longterm ramifications of reduced access to care for severe acute physical and mental health conditions. Maintaining access to primary care is key to future public health planning in relation to the pandemic.</jats:sec

Indirect acute effects of the COVID-19 pandemic on physical and mental health in the UK: a population-based study.

BACKGROUND: There are concerns that the response to the COVID-19 pandemic in the UK might have worsened physical and mental health, and reduced use of health services. However, the scale of the problem is unquantified, impeding development of effective mitigations. We aimed to ascertain what has happened to general practice contacts for acute physical and mental health outcomes during the pandemic. METHODS: Using de-identified electronic health records from the Clinical Research Practice Datalink (CPRD) Aurum (covering 13% of the UK population), between 2017 and 2020, we calculated weekly primary care contacts for selected acute physical and mental health conditions: anxiety, depression, self-harm (fatal and non-fatal), severe mental illness, eating disorder, obsessive-compulsive disorder, acute alcohol-related events, asthma exacerbation, chronic obstructive pulmonary disease exacerbation, acute cardiovascular events (cerebrovascular accident, heart failure, myocardial infarction, transient ischaemic attacks, unstable angina, and venous thromboembolism), and diabetic emergency. Primary care contacts included remote and face-to-face consultations, diagnoses from hospital discharge letters, and secondary care referrals, and conditions were identified through primary care records for diagnoses, symptoms, and prescribing. Our overall study population included individuals aged 11 years or older who had at least 1 year of registration with practices contributing to CPRD Aurum in the specified period, but denominator populations varied depending on the condition being analysed. We used an interrupted time-series analysis to formally quantify changes in conditions after the introduction of population-wide restrictions (defined as March 29, 2020) compared with the period before their introduction (defined as Jan 1, 2017 to March 7, 2020), with data excluded for an adjustment-to-restrictions period (March 8-28). FINDINGS: The overall population included 9 863 903 individuals on Jan 1, 2017, and increased to 10 226 939 by Jan 1, 2020. Primary care contacts for almost all conditions dropped considerably after the introduction of population-wide restrictions. The largest reductions were observed for contacts for diabetic emergencies (odds ratio 0·35 [95% CI 0·25-0·50]), depression (0·53 [0·52-0·53]), and self-harm (0·56 [0·54-0·58]). In the interrupted time-series analysis, with the exception of acute alcohol-related events (0·98 [0·89-1·10]), there was evidence of a reduction in contacts for all conditions (anxiety 0·67 [0·66-0·67], eating disorders 0·62 [0·59-0·66], obsessive-compulsive disorder [0·69 [0·64-0·74]], self-harm 0·56 [0·54-0·58], severe mental illness 0·80 [0·78-0·83], stroke 0·59 [0·56-0·62], transient ischaemic attack 0·63 [0·58-0·67], heart failure 0·62 [0·60-0·64], myocardial infarction 0·72 [0·68-0·77], unstable angina 0·72 [0·60-0·87], venous thromboembolism 0·94 [0·90-0·99], and asthma exacerbation 0·88 [0·86-0·90]). By July, 2020, except for unstable angina and acute alcohol-related events, contacts for all conditions had not recovered to pre-lockdown levels. INTERPRETATION: There were substantial reductions in primary care contacts for acute physical and mental conditions following the introduction of restrictions, with limited recovery by July, 2020. Further research is needed to ascertain whether these reductions reflect changes in disease frequency or missed opportunities for care. Maintaining health-care access should be a key priority in future public health planning, including further restrictions. The conditions we studied are sufficiently severe that any unmet need will have substantial ramifications for the people with the conditions as well as health-care provision. FUNDING: Wellcome Trust Senior Fellowship, Health Data Research UK

Clinical coding of long COVID in primary care 2020-2023 in a cohort of 19 million adults: an OpenSAFELY analysis

BACKGROUND: Long COVID is the patient-coined term for the persistent symptoms of COVID-19 illness for weeks, months or years following the acute infection. There is a large burden of long COVID globally from self-reported data, but the epidemiology, causes and treatments remain poorly understood. Primary care is used to help identify and treat patients with long COVID and therefore Electronic Health Records (EHRs) of past COVID-19 patients could be used to help fill these knowledge gaps. We aimed to describe the incidence and differences in demographic and clinical characteristics in recorded long COVID in primary care records in England. METHODS: With the approval of NHS England we used routine clinical data from over 19 million adults in England linked to SARS-COV-2 test result, hospitalisation and vaccination data to describe trends in the recording of 16 clinical codes related to long COVID between November 2020 and January 2023. Using OpenSAFELY, we calculated rates per 100,000 person-years and plotted how these changed over time. We compared crude and adjusted (for age, sex, 9 NHS regions of England, and the dominant variant circulating) rates of recorded long COVID in patient records between different key demographic and vaccination characteristics using negative binomial models. FINDINGS: We identified a total of 55,465 people recorded to have long COVID over the study period, which included 20,025 diagnoses codes and 35,440 codes for further assessment. The incidence of new long COVID records increased steadily over 2021, and declined over 2022. The overall rate per 100,000 person-years was 177.5 cases in women (95% CI: 175.5-179) and 100.5 in men (99.5-102). The majority of those with a long COVID record did not have a recorded positive SARS-COV-2 test 12 or more weeks before the long COVID record. INTERPRETATION: In this descriptive study, EHR recorded long COVID was very low between 2020 and 2023, and incident records of long COVID declined over 2022. Using EHR diagnostic or referral codes unfortunately has major limitations in identifying and ascertaining true cases and timing of long COVID. FUNDING: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073)

Impact of long COVID on health-related quality-of-life: an OpenSAFELY population cohort study using patient-reported outcome measures (OpenPROMPT).

BACKGROUND: Long COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. We aimed to evaluate and estimate the differences in health impacts of long COVID across sociodemographic categories and quantify this in Quality-Adjusted Life-Years (QALYs), widely used measures across health systems. METHODS: With the approval of NHS England, we utilised OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. FINDINGS: The total OpenPROMPT cohort consisted of 7575 individuals who consented to data collection, with which we used data from 6070 participants who completed a baseline research questionnaire where 24.6% self-reported long COVID. In multivariable regressions, long COVID had a consistent impact on HRQoL, showing a higher likelihood or odds of reporting loss in quality-of-life (Odds Ratio (OR): 4.7, 95% CI: 3.72-5.93) compared with people who did not report long COVID. Reporting a disability was the largest predictor of losses of HRQoL (OR: 17.7, 95% CI: 10.37-30.33) across survey responses. Self-reported long COVID was associated with an 0.37 QALM loss. INTERPRETATION: We found substantial impacts on quality-of-life due to long COVID, representing a major burden on patients and the health service. We highlight the need for continued support and research for long COVID, as HRQoL scores compared unfavourably to patients with conditions such as multiple sclerosis, heart failure, and renal disease. FUNDING: This research was supported by the National Institute for Health and Care Research (NIHR) (OpenPROMPT: COV-LT2-0073)