Three-dimensional electronic microfliers inspired by wind-dispersed seeds.

Large, distributed collections of miniaturized, wireless electronic devices1,2 may form the basis of future systems for environmental monitoring3, population surveillance4, disease management5 and other applications that demand coverage over expansive spatial scales. Aerial schemes to distribute the components for such networks are required, and-inspired by wind-dispersed seeds6-we examined passive structures designed for controlled, unpowered flight across natural environments or city settings. Techniques in mechanically guided assembly of three-dimensional (3D) mesostructures7-9 provide access to miniature, 3D fliers optimized for such purposes, in processes that align with the most sophisticated production techniques for electronic, optoelectronic, microfluidic and microelectromechanical technologies. Here we demonstrate a range of 3D macro-, meso- and microscale fliers produced in this manner, including those that incorporate active electronic and colorimetric payloads. Analytical, computational and experimental studies of the aerodynamics of high-performance structures of this type establish a set of fundamental considerations in bio-inspired design, with a focus on 3D fliers that exhibit controlled rotational kinematics and low terminal velocities. An approach that represents these complex 3D structures as discrete numbers of blades captures the essential physics in simple, analytical scaling forms, validated by computational and experimental results. Battery-free, wireless devices and colorimetric sensors for environmental measurements provide simple examples of a wide spectrum of applications of these unusual concepts.

A pooled testing strategy for identifying SARS-CoV-2 at low prevalence.

Suppressing infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will probably require the rapid identification and isolation of individuals infected with the virus on an ongoing basis. Reverse-transcription polymerase chain reaction (RT-PCR) tests are accurate but costly, which makes the regular testing of every individual expensive. These costs are a challenge for all countries around the world, but particularly for low-to-middle-income countries. Cost reductions can be achieved by pooling (or combining) subsamples and testing them in groups1-7. A balance must be struck between increasing the group size and retaining test sensitivity, as sample dilution increases the likelihood of false-negative test results for individuals with a low viral load in the sampled region at the time of the test8. Similarly, minimizing the number of tests to reduce costs must be balanced against minimizing the time that testing takes, to reduce the spread of the infection. Here we propose an algorithm for pooling subsamples based on the geometry of a hypercube that, at low prevalence, accurately identifies individuals infected with SARS-CoV-2 in a small number of tests and few rounds of testing. We discuss the optimal group size and explain why, given the highly infectious nature of the disease, largely parallel searches are preferred. We report proof-of-concept experiments in which a positive subsample was detected even when diluted 100-fold with negative subsamples (compared with 30-48-fold dilutions described in previous studies9-11). We quantify the loss of sensitivity due to dilution and discuss how it may be mitigated by the frequent re-testing of groups, for example. With the use of these methods, the cost of mass testing could be reduced by a large factor. At low prevalence, the costs decrease in rough proportion to the prevalence. Field trials of our approach are under way in Rwanda and South Africa. The use of group testing on a massive scale to monitor infection rates closely and continually in a population, along with the rapid and effective isolation of people with SARS-CoV-2 infections, provides a promising pathway towards the long-term control of coronavirus disease 2019 (COVID-19).

Covid-19 Surveillance Testing and Resident Outcomes in Nursing Homes.

BACKGROUND: Despite widespread adoption of surveillance testing for coronavirus disease 2019 (Covid-19) among staff members in skilled nursing facilities, evidence is limited regarding its relationship with outcomes among facility residents. METHODS: Using data obtained from 2020 to 2022, we performed a retrospective cohort study of testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among staff members in 13,424 skilled nursing facilities during three pandemic periods: before vaccine approval, before the B.1.1.529 (omicron) variant wave, and during the omicron wave. We assessed staff testing volumes during weeks without Covid-19 cases relative to other skilled nursing facilities in the same county, along with Covid-19 cases and deaths among residents during potential outbreaks (defined as the occurrence of a case after 2 weeks with no cases). We reported adjusted differences in outcomes between high-testing facilities (90th percentile of test volume) and low-testing facilities (10th percentile). The two primary outcomes were the weekly cumulative number of Covid-19 cases and related deaths among residents during potential outbreaks. RESULTS: During the overall study period, 519.7 cases of Covid-19 per 100 potential outbreaks were reported among residents of high-testing facilities as compared with 591.2 cases among residents of low-testing facilities (adjusted difference, -71.5; 95% confidence interval [CI], -91.3 to -51.6). During the same period, 42.7 deaths per 100 potential outbreaks occurred in high-testing facilities as compared with 49.8 deaths in low-testing facilities (adjusted difference, -7.1; 95% CI, -11.0 to -3.2). Before vaccine availability, high- and low-testing facilities had 759.9 cases and 1060.2 cases, respectively, per 100 potential outbreaks (adjusted difference, -300.3; 95% CI, -377.1 to -223.5), along with 125.2 and 166.8 deaths (adjusted difference, -41.6; 95% CI, -57.8 to -25.5). Before the omicron wave, the numbers of cases and deaths were similar in high- and low-testing facilities; during the omicron wave, high-testing facilities had fewer cases among residents, but deaths were similar in the two groups. CONCLUSIONS: Greater surveillance testing of staff members at skilled nursing facilities was associated with clinically meaningful reductions in Covid-19 cases and deaths among residents, particularly before vaccine availability.

Burden of Typhoid and Paratyphoid Fever in India.

BACKGROUND: In 2017, more than half the cases of typhoid fever worldwide were projected to have occurred in India. In the absence of contemporary population-based data, it is unclear whether declining trends of hospitalization for typhoid in India reflect increased antibiotic treatment or a true reduction in infection. METHODS: From 2017 through 2020, we conducted weekly surveillance for acute febrile illness and measured the incidence of typhoid fever (as confirmed on blood culture) in a prospective cohort of children between the ages of 6 months and 14 years at three urban sites and one rural site in India. At an additional urban site and five rural sites, we combined blood-culture testing of hospitalized patients who had a fever with survey data regarding health care use to estimate incidence in the community. RESULTS: A total of 24,062 children who were enrolled in four cohorts contributed 46,959 child-years of observation. Among these children, 299 culture-confirmed typhoid cases were recorded, with an incidence per 100,000 child-years of 576 to 1173 cases in urban sites and 35 in rural Pune. The estimated incidence of typhoid fever from hospital surveillance ranged from 12 to 1622 cases per 100,000 child-years among children between the ages of 6 months and 14 years and from 108 to 970 cases per 100,000 person-years among those who were 15 years of age or older. Salmonella enterica serovar Paratyphi was isolated from 33 children, for an overall incidence of 68 cases per 100,000 child-years after adjustment for age. CONCLUSIONS: The incidence of typhoid fever in urban India remains high, with generally lower estimates of incidence in most rural areas. (Funded by the Bill and Melinda Gates Foundation; NSSEFI Clinical Trials Registry of India number, CTRI/2017/09/009719; ISRCTN registry number, ISRCTN72938224.).

Sex Differences in Trends in Stroke Recurrence and Postrecurrence Mortality 2000-2020: Population-Based Brain Attack Surveillance in Corpus Christi Project.

OBJECTIVE: This study was undertaken to delineate 21-year sex-specific trends in recurrence and postrecurrence mortality. METHODS: Between 2000 and 2020, first-ever ischemic stroke (IS) patients, ascertained from the population-based BASIC (Brain Attack Surveillance in Corpus Christi) project in South Texas, were followed for recurrent stroke and all-cause mortality until December 31, 2020. Multivariable regression models with an interaction between calendar year and sex were used to estimate sex-specific trends and sex differences in recurrence and postrecurrence mortality. RESULTS: Of the 6,057 IS patients (median age = 69 years, 49.8% women), 654 (10.8%) had a recurrence and 399 (47.7%) had postrecurrence mortality during 5 years of follow-up. In 2000, women had 2.5% higher albeit non-statistically significant 5-year risk of recurrence than men in absolute scale. With the trend declining in women by 7.6% (95% confidence interval [CI] = -10.8 to -4.5%) and in men by 3.6% (95% CI = -6.5% to -0.7%), the risk at the end of the study period was 1.5% (95% CI = -0.3% to 3.6%) lower among women than men. For postrecurrence mortality, the risk was 10.2% lower among women in 2000, but the sex difference was 3.3% by the end of the period, which was due to a larger overall increase in the risk among women than men over the entire time period. INTERPRETATION: The declines in recurrent stroke suggest successful secondary stroke prevention, especially in women. However, the continued high postrecurrence mortality among both sexes at the end of study period emphasizes the need for ongoing interventions to improve prognosis in those who have had recurrent cerebrovascular events. ANN NEUROL 2024;96:332-342.

Half of US population exposed to adverse lead levels in early childhood.

SignificanceConsiderable effort is expended to protect today's children from lead exposure, but there is little evidence on the harms past lead exposures continue to hold for yesterday's children, who are victims of what we term legacy lead exposures. We estimate that over 170 million Americans alive today were exposed to high-lead levels in early childhood, several million of whom were exposed to five-plus times the current reference level. Our estimates allow future work to plan for the health needs of these Americans and to inform estimation of the true contributions of lead exposure to population health. We estimate population-level effects on IQ loss and find that lead is responsible for the loss of 824,097,690 IQ points as of 2015.

Disparities in Tuberculosis Incidence by Race and Ethnicity Among the U.S.-Born Population in the United States, 2011 to 2021 : An Analysis of National Disease Registry Data.

BACKGROUND: Elevated tuberculosis (TB) incidence rates have recently been reported for racial/ethnic minority populations in the United States. Tracking such disparities is important for assessing progress toward national health equity goals and implementing change. OBJECTIVE: To quantify trends in racial/ethnic disparities in TB incidence among U.S.-born persons. DESIGN: Time-series analysis of national TB registry data for 2011 to 2021. SETTING: United States. PARTICIPANTS: U.S.-born persons stratified by race/ethnicity. MEASUREMENTS: TB incidence rates, incidence rate differences, and incidence rate ratios compared with non-Hispanic White persons; excess TB cases (calculated from incidence rate differences); and the index of disparity. Analyses were stratified by sex and by attribution of TB disease to recent transmission and were adjusted for age, year, and state of residence. RESULTS: In analyses of TB incidence rates for each racial/ethnic population compared with non-Hispanic White persons, incidence rate ratios were as high as 14.2 (95% CI, 13.0 to 15.5) among American Indian or Alaska Native (AI/AN) females. Relative disparities were greater for females, younger persons, and TB attributed to recent transmission. Absolute disparities were greater for males. Excess TB cases in 2011 to 2021 represented 69% (CI, 66% to 71%) and 62% (CI, 60% to 64%) of total cases for females and males, respectively. No evidence was found to indicate that incidence rate ratios decreased over time, and most relative disparity measures showed small, statistically nonsignificant increases. LIMITATION: Analyses assumed complete TB case diagnosis and self-report of race/ethnicity and were not adjusted for medical comorbidities or social determinants of health. CONCLUSION: There are persistent disparities in TB incidence by race/ethnicity. Relative disparities were greater for AI/AN persons, females, and younger persons, and absolute disparities were greater for males. Eliminating these disparities could reduce overall TB incidence by more than 60% among the U.S.-born population. PRIMARY FUNDING SOURCE: Centers for Disease Control and Prevention.

Pooled testing efficiency increases with test frequency.

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by x times only increases expected tests by around [Formula: see text] However, this calculation omits a further benefit of frequent testing: Removing infections from the population lowers intragroup transmission, which lowers infection probability and generates further efficiency. For this reason, increasing testing frequency can paradoxically reduce total testing cost. Our calculations are based on the assumption that infection rates are known, but predicting these rates is challenging in a fast-moving pandemic. However, given that frequent testing naturally suppresses the mean and variance of infection rates, we show that our results are very robust to uncertainty and misprediction. Finally, we note that efficiency further increases given natural sampling pools (e.g., workplaces, classrooms) that induce correlated risk via local transmission. We conclude that frequent pooled testing using natural groupings is a cost-effective way to provide consistent testing of a population to suppress infection risk in a pandemic.

Lyme Disease Surveillance and Epidemiology in the United States: A Historical Perspective.

In the 40 years since Steere and colleagues first described Lyme disease, the illness has increased in incidence and distribution to become the most common vector-borne disease in the United States. Public health officials have developed, implemented, and revised surveillance systems to describe and monitor the condition. Much has been learned about the epidemiology of the illness, despite practical and logistical constraints that have encumbered the collection and interpretation of surveillance data. Future development of automated data collection from electronic health records as a source of surveillance and clinical information will address practical challenges and help answer ongoing questions about complications and persistent symptoms. Robust surveillance will be essential to monitor the effectiveness and safety of future vaccines and other preventive measures.

Using Passive Surveillance to Maintain Elimination as a Public Health Problem for Neglected Tropical Diseases: A Model-Based Exploration.

BACKGROUND: Great progress is being made toward the goal of elimination as a public health problem for neglected tropical diseases such as leprosy, human African trypanosomiasis, Buruli ulcer, and visceral leishmaniasis, which relies on intensified disease management and case finding. However, strategies for maintaining this goal are still under discussion. Passive surveillance is a core pillar of a long-term, sustainable surveillance program. METHODS: We use a generic model of disease transmission with slow epidemic growth rates and cases detected through severe symptoms and passive detection to evaluate under what circumstances passive detection alone can keep transmission under control. RESULTS: Reducing the period of infectiousness due to decreasing time to treatment has a small effect on reducing transmission. Therefore, to prevent resurgence, passive surveillance needs to be very efficient. For some diseases, the treatment time and level of passive detection needed to prevent resurgence is unlikely to be obtainable. CONCLUSIONS: The success of a passive surveillance program crucially depends on what proportion of cases are detected, how much of their infectious period is reduced, and the underlying reproduction number of the disease. Modeling suggests that relying on passive detection alone is unlikely to be enough to maintain elimination goals.

Assessing the Impact of the 2020 Council of State and Territorial Epidemiologists Case Definition for Pertussis on Reported Pertussis Cases.

BACKGROUND: In 2020, the Council of State and Territorial Epidemiologists (CSTE) pertussis case definition was modified; the main change was classifying polymerase chain reaction (PCR)-positive cases as confirmed, regardless of cough duration. Pertussis data reported through Enhanced Pertussis Surveillance (EPS) in 7 sites and the National Notifiable Diseases Surveillance System (NNDSS) were used to evaluate the impact of the new case definition. METHODS: We compared the number of EPS cases with cough onset in 2020 to the number that would have been reported based on the prior (2014) CSTE case definition. To assess the impact of the change nationally, the proportion of EPS cases newly reportable under the 2020 CSTE case definition was applied to 2020 NNDSS data to estimate how many additional cases were captured nationally. RESULTS: Among 442 confirmed and probable cases reported to EPS states in 2020, 42 (9.5%) were newly reportable according to the 2020 case definition. Applying this proportion to the 6124 confirmed and probable cases reported nationally in 2020, we estimated that the new definition added 582 cases. Had the case definition not changed, reported cases in 2020 would have decreased by 70% from 2019; the observed decrease was 67%. CONCLUSIONS: Despite a substantial decrease in reported pertussis cases in the setting of coronavirus disease 2019 (COVID-19), our data show that the 2020 pertussis case definition change resulted in additional case reporting compared with the previous case definition, providing greater opportunities for public health interventions such as prophylaxis of close contacts.

Electronic Health Record Data for Lyme Disease Surveillance, Massachusetts, USA, 2017-2018.

Lyme disease surveillance based on provider and laboratory reports underestimates incidence. We developed an algorithm for automating surveillance using electronic health record data. We identified potential Lyme disease markers in electronic health record data (laboratory tests, diagnosis codes, prescriptions) from January 2017-December 2018 in 2 large practice groups in Massachusetts, USA. We calculated their sensitivities and positive predictive values (PPV), alone and in combination, relative to medical record review. Sensitivities ranged from 57% (95% CI 47%-69%) for immunoassays to 87% (95% CI 70%-100%) for diagnosis codes. PPVs ranged from 53% (95% CI 43%-61%) for diagnosis codes to 58% (95% CI 50%-66%) for immunoassays. The combination of a diagnosis code and antibiotics within 14 days or a positive Western blot had a sensitivity of 100% (95% CI 86%-100%) and PPV of 82% (95% CI 75%-89%). This algorithm could make Lyme disease surveillance more efficient and consistent.

Use of Open-Source Epidemic Intelligence for Infectious Disease Outbreaks, Ukraine, 2022.

Formal infectious disease surveillance in Ukraine has been disrupted by Russia's 2022 invasion, leading to challenges with tracking and containing epidemics. To analyze the effects of the war on infectious disease epidemiology, we used open-source data from EPIWATCH, an artificial intelligence early-warning system. We analyzed patterns of infectious diseases and syndromes before (November 1, 2021-February 23, 2022) and during (February 24-July 31, 2022) the conflict. We compared case numbers for the most frequently reported diseases with numbers from formal sources and found increases in overall infectious disease reports and in case numbers of cholera, botulism, tuberculosis, HIV/AIDS, rabies, and salmonellosis during compared with before the invasion. During the conflict, although open-source intelligence captured case numbers for epidemics, such data (except for diphtheria) were unavailable/underestimated by formal surveillance. In the absence of formal surveillance during military conflicts, open-source data provide epidemic intelligence useful for infectious disease control.

Computerized Decision Support Systems Informing Community-Acquired Pneumonia Surveillance, France, 2017-2023.

We show the value of real-time data generated by a computerized decision support system in primary care in strengthening pneumonia surveillance. The system showed a 66% (95% CI 64%-67%) increase in community-acquired pneumonia from 2018 to 2023 for the population of France, 1 month before a national alert was issued.

Participatory, Virologic, and Wastewater Surveillance Data to Assess Underestimation of COVID-19 Incidence, Germany, 2020-2024.

Using participatory, virologic, and wastewater surveillance systems, we estimated when and to what extent reported data of adult COVID-19 cases underestimated COVID-19 incidence in Germany. We also examined how case underestimation evolved over time. Our findings highlight how community-based surveillance systems can complement official notification systems for respiratory disease dynamics.

Electronic Health Record-Based Algorithm for Monitoring Respiratory Virus-Like Illness.

Viral respiratory illness surveillance has traditionally focused on single pathogens (e.g., influenza) and required fever to identify influenza-like illness (ILI). We developed an automated system applying both laboratory test and syndrome criteria to electronic health records from 3 practice groups in Massachusetts, USA, to monitor trends in respiratory viral-like illness (RAVIOLI) across multiple pathogens. We identified RAVIOLI syndrome using diagnosis codes associated with respiratory viral testing or positive respiratory viral assays or fever. After retrospectively applying RAVIOLI criteria to electronic health records, we observed annual winter peaks during 2015-2019, predominantly caused by influenza, followed by cyclic peaks corresponding to SARS-CoV-2 surges during 2020-2024, spikes in RSV in mid-2021 and late 2022, and recrudescent influenza in late 2022 and 2023. RAVIOLI rates were higher and fluctuations more pronounced compared with traditional ILI surveillance. RAVIOLI broadens the scope, granularity, sensitivity, and specificity of respiratory viral illness surveillance compared with traditional ILI surveillance.

Implementation of a Hepatocellular Carcinoma Surveillance Program in a Community-Based Integrated Health System in Patients With Hepatitis C Cirrhosis.

INTRODUCTION: Underutilization of hepatocellular cancer (HCC) surveillance has been reported, although data evaluating interventions to improve surveillance are sparse. We assessed the effect of a population-based HCC surveillance program on HCC surveillance utilization and outcomes. METHODS: In this retrospective cohort study, we assessed preinclusion and postinclusion HCC surveillance patterns among 597 patients with hepatitis C virus cirrhosis enrolled in a program at an integrated health system between 2013 and 2020. Adequate surveillance was defined as at least 5 surveillance studies within 36 months pre-enrollment and postenrollment; a secondary outcome was proportion of time covered by surveillance over 36 months. Tumor size, stage, and receipt of curative therapy were compared between HCC detected on the first imaging examination (prevalent HCC) and surveillance-detected HCC (incident HCC). We performed Kaplan-Meier analysis and multivariable competing risk analysis to characterize the association between surveillance and mortality. RESULTS: The surveillance program significantly improved surveillance completion (77.6% vs 5.0%, P < 0.001) and proportion time covered (80.9% vs 15.8%, P < 0.001). Compared with prevalent HCC, surveillance-detected cases were more likely unifocal (77.8% vs 44.8%, P < 0.001), early-stage (85.2% vs 44.8%, P < 0.001), with smaller maximum diameter (median 2.3 vs 3.2 cm), and more likely to undergo curative therapy (92.5% vs 72.4% P = 0.010). Survival was improved compared with prevalent cases hazard ratio (HR) 0.23 (0.11-0.51) after adjusting for age and Model for End Stage Liver Disease score. DISCUSSION: Implementation of a population-based program resulted in significant improvement in HCC surveillance use and clinical outcomes among patients with hepatitis C virus cirrhosis. These findings may inform similar interventions by other healthcare systems.

English tweets on allergy: Content analysis and association with surveillance data.

BACKGROUND: Analysis of X (formerly Twitter) posts can inform on the interest/perceptions that social media users have on health subjects. In this study, we aimed to analyse tweets on allergic conditions, comparing them with surveillance data. METHODS: We retrieved tweets from England on "allergy," "asthma," and "allergic rhinitis," published between 2016 and 2021. We estimated the correlation between the frequency of tweets on "asthma" and "allergic rhinitis" and English surveillance data on the incidence of asthma and allergic rhinitis medical visits. We performed sentiment analysis, computing a score informing on the emotional tone of assessed tweets. We applied a topic modelling approach to identify topics (clusters of words frequently occurring together) for tweets on each assessed condition. RESULTS: We analysed a total of 13,605 tweets on "allergy," 7767 tweets on "asthma," and 11,974 tweets on "allergic rhinitis." Food-related words were preponderant on tweets on "allergy," while "eyes" was the most frequent meaningful word on "allergy rhinitis" tweets. We observed seasonal patterns for tweets on "allergic rhinitis," both in their frequency and sentiment - the incidence of allergic rhinitis medical visits was moderately to strongly correlated with the frequency (ρ = 0.866) and sentiment (ρ = -0.474) of tweets on "allergic rhinitis." For tweets on "asthma," no such patterns/correlations were observed. The average sentiment score was negative for all assessed conditions, ranging from -0.004 ("asthma") to -0.083 ("allergic rhinitis"). CONCLUSIONS: Tweets on "allergic rhinitis" displayed a seasonal pattern regarding their frequency and sentiment, which correlated with surveillance data. No such patterns were observed for "asthma."

Surveillance Strategies After Primary Treatment for Patients with Invasive Lobular Carcinoma of the Breast: Method of Local Recurrence Detection After Breast-Conserving Surgery.

BACKGROUND: Invasive lobular carcinoma (ILC) is the second most common subtype of breast cancer. Although mammography is known to have low sensitivity for ILC, there are no data to guide the optimal surveillance after treatment. We explored surveillance strategies after breast-conserving surgery (BCS) for ILC and determined the proportion of imaging-detected recurrences versus interval cancers. METHODS: From an institutional database of 813 women, we retrospectively identified patients who underwent BCS for stage I-III ILC and subsequently had a recurrence. We categorized patients by surveillance strategy and determined the modality of recurrence detection. Interval cancer rates for local recurrences were compared across surveillance strategies using the Chi-square test. We evaluated overall survival with the log-rank test and a Cox proportional hazards model. RESULTS: We included 58 patients with ILC who had a recurrence after BCS. Of these, 22 (37.9%) had local recurrence, 27 (46.6%) had distant recurrence, and 9 (15.5%) had both local and distant recurrence. Most patients underwent routine mammographic surveillance (65.2%), with 19.6% having supplemental breast magnetic resonance imaging (MRI) and 15.2% having no surveillance. The interval cancer rate was significantly higher in the mammographic surveillance group compared with the MRI surveillance group (61.9% vs. 16.7%; p < 0.001). CONCLUSION: In this study of patients with recurrence after BCS for primary treatment of stage I-III ILC, we found that most local recurrences were not detected by surveillance mammography. These data support further investigation of supplemental imaging beyond mammography specifically for patients with ILC who undergo BCS.

Mental health and use of psychotropic prescription drugs in adult patients with primary immune thrombocytopenia: a nationwide population-based cohort study.

Patients with primary immune thrombocytopenia (ITP) suffer from reduced survival and quality of life, but the underlying reasons for this are largely undescribed. Mental health and the use of psychotropic drugs in ITP is unknown. We investigated the risk of hospital-registered mental health events including fatigue and the use of psychotropic drugs in adult patients with ITP compared with the general population, using nationwide registry-data. We identified 3,749 patients with ITP and 149,849 age- and sex-matched general population comparators in the Danish Health Registries in the period 1997-2016. The median age was 60 years (interquartile range [IQR], 40-73) and 53% were women. We followed the individuals for incident mental health events and estimated the use of psychotropic drugs over calendar-years and in temporal relation to diagnosis of ITP. The first year cumulative incidence of any mental health event was 2.3% (95% confidence interval [CI]: 1.9-2.9) in patients and 0.7% (95% CI: 0.6-0.7) in comparators, yielding an adjusted cause-specific hazard ratio (csHR) of 3.57 (95% CI: 2.84-4.50). The corresponding estimates for depression were 1.2% (95% CI: 0.9-1.6) and 0.3% (0.3-0.4) respectively, with an adjusted csHR of 3.53 (95% CI: 2.56-4.85). We found similar findings for anxiety and fatigue, but risks generally diminished after 1-5 years. The use of opioids, antidepressants, and benzodiazepines increased in temporal relation to diagnosis of ITP. The risk of mental health events and the use of psychotropic drugs is higher in adult patients with ITP compared with the general population, and has a temporal relation to diagnosis of ITP emphasizing that mental health in ITP is a concern.