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Pirkis, Jane, Gunnell, David, Shin, Sangsoo, DelPozo-Banos, Marcos, Arya, Vikas, Analuisa Aguilar, Pablo, Appleby, Louis, Arafat, S. M. Yasir, Arensman, Ella, Ayuso-Mateos, Jose Luis, Balhara, Yatan Pal Singh, Bantjes, Jason, Baran, Anna, Behera, Chittaranjan, Bertolote, Jose, Borges, Guilherme, Bray, Michael, Brečić, Petrana, Caine, Eric D.; Calati, Raffaella, Carli, Vladimir, Castelpietra, Giulio, Chan, Lai Fong, Chang, Shu-Sen, Colchester, David, Coss-Guzmán, Maria, Crompton, David, Curkovic, Marko, Dandona, Rakhi, De Jaegere, Eva, De Leo, Diego, Deisenhammer, Eberhard, Dwyer, Jeremy, Erlangsen, Annette, Faust, Jeremy, Fornaro, Michele, Fortune, Sarah, Garrett, Andrew, Gentile, Guendalina, Gerstner, Rebekka, Gilissen, Renske, Gould, Madelyn, Gupta, Sudhir Kumar, Hawton, Keith, Holz, Franziska, Kamenshchikov, Iurii, Kapur, Navneet, Kasal, Alexandr, Khan, Murad, Kirtley, Olivia, Knipe, Duleeka, Kolves, Kairi, Kölzer, Sarah, Krivda, Hryhorii, Leske, Stuart, Madeddu, Fabio, Marshall, Andrew, Memon, Anjum, Mittendorfer-Rutz, Ellenor, Nestadt, Paul, Neznanov, Nikolay, Niederkrotenthaler, Thomas, Nielsen, Emma, Nordentoft, Merete, Oberlerchner, Herwig, O'Connor, Rory, Papsdorf, Rainer, Partonen, Timo, Michael, Phillips, Platt, Steve, Portzky, Gwendolyn, Psota, Georg, Qin, Ping, Radeloff, Daniel, Reif, Andreas, Reif-Leonhard, Christine, Rezaeian, Mohsen, Román-Vázquez, Nayda, Roskar, Saska, Rozanov, Vsevolod, Sara, Grant, Scavacini, Karen, Schneider, Barbara, Semenova, Natalia, Sinyor, Mark, Tambuzzi, Stefano, Townsend, Ellen, Ueda, Michiko, Wasserman, Danuta, Webb, Roger T.; Winkler, Petr, Yip, Paul S. F.; Zalsman, Gil, Zoja, Riccardo, John, Ann, Spittal, Matthew J..
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-331684

ABSTRACT

Background When the COVID-19 pandemic began there were concerns that suicides might rise, but predicted increases were not generally observed in the pandemic’s early months. However, the picture may be changing and patterns may vary across demographic groups. We aimed to provide an up-to-date, granular picture of the impact of COVID-19 on suicides globally.Methods We identified suicide data from official public-sector sources for countries/areas-within-countries. We used interrupted time series (ITS) analyses to model the association between the pandemic’s emergence and total suicides and suicides by sex-, age- and sex-by-age in each country/area-within-country. We compared the observed number of suicides to the expected number in the pandemic’s first nine and first 10-15 months and used meta-regression to explore sources of variation.Findings We sourced data from 33 countries (24 high-income, six upper-middle-income, three lower-middle-income). There was no evidence of greater-than-expected numbers of suicides in the majority of countries/areas-within-countries in any analysis;more commonly, there was evidence of lower-than-expected numbers. Certain sex, age and sex-by-age groups stood out as potentially concerning, but these were not consistent across countries/areas-within-countries. In the meta-regression, different patterns were not explained by countries’ COVID-19 mortality rate, stringency of public health response, level of economic support, or presence of a national suicide prevention strategy. They were also not explained by countries’ income level, although the meta-regression only included data from high-income and upper-middle-income countries, and there were suggestions from the ITS analyses that lower-middle-income countries fared less well.Interpretation Although there are some countries/areas-within-countries where overall suicide numbers and numbers for certain sex- and age-based groups are greater-than-expected, these are in the minority. Any upward movement in suicide numbers in any place or group is concerning, and we need to remain alert to and respond to changes as the pandemic and its mental health and economic consequences continue.

3.
EClinicalMedicine ; 32: 100741, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-1071273

ABSTRACT

BACKGROUND: Suicides by any method, plus 'nonsuicide' fatalities from drug self-intoxication (estimated from selected forensically undetermined and 'accidental' deaths), together represent self-injury mortality (SIM)-fatalities due to mental disorders or distress. SIM is especially important to examine given frequent undercounting of suicides amongst drug overdose deaths. We report suicide and SIM trends in the United States of America (US) during 1999-2018, portray interstate rate trends, and examine spatiotemporal (spacetime) diffusion or spread of the drug self-intoxication component of SIM, with attention to potential for differential suicide misclassification. METHODS: For this state-based, cross-sectional, panel time series, we used de-identified manner and underlying cause-of-death data for the 50 states and District of Columbia (DC) from CDC's Wide-ranging Online Data for Epidemiologic Research. Procedures comprised joinpoint regression to describe national trends; Spearman's rank-order correlation coefficient to assess interstate SIM and suicide rate congruence; and spacetime hierarchical modelling of the 'nonsuicide' SIM component. FINDINGS: The national annual average percentage change over the observation period in the SIM rate was 4.3% (95% CI: 3.3%, 5.4%; p<0.001) versus 1.8% (95% CI: 1.6%, 2.0%; p<0.001) for the suicide rate. By 2017/2018, all states except Nebraska (19.9) posted a SIM rate of at least 21.0 deaths per 100,000 population-the floor of the rate range for the top 5 ranking states in 1999/2000. The rank-order correlation coefficient for SIM and suicide rates was 0.82 (p<0.001) in 1999/2000 versus 0.34 (p = 0.02) by 2017/2018. Seven states in the West posted a ≥ 5.0% reduction in their standardised mortality ratios of 'nonsuicide' drug fatalities, relative to the national ratio, and 6 states from the other 3 major regions a >6.0% increase (p<0.05). INTERPRETATION: Depiction of rising SIM trends across states and major regions unmasks a burgeoning national mental health crisis. Geographic variation is plausibly a partial product of local heterogeneity in toxic drug availability and the quality of medicolegal death investigations. Like COVID-19, the nation will only be able to prevent SIM by responding with collective, comprehensive, systemic approaches. Injury surveillance and prevention, mental health, and societal well-being are poorly served by the continuing segregation of substance use disorders from other mental disorders in clinical medicine and public health practice. FUNDING: This study was partially funded by the National Centre for Injury Prevention and Control, US Centers for Disease Control and Prevention (R49CE002093) and the US National Institute on Drug Abuse (1UM1DA049412-01; 1R21DA046521-01A1).

4.
J Med Internet Res ; 22(11): e22600, 2020 11 24.
Article in English | MEDLINE | ID: covidwho-969095

ABSTRACT

BACKGROUND: The COVID-19 pandemic has caused several disruptions in personal and collective lives worldwide. The uncertainties surrounding the pandemic have also led to multifaceted mental health concerns, which can be exacerbated with precautionary measures such as social distancing and self-quarantining, as well as societal impacts such as economic downturn and job loss. Despite noting this as a "mental health tsunami", the psychological effects of the COVID-19 crisis remain unexplored at scale. Consequently, public health stakeholders are currently limited in identifying ways to provide timely and tailored support during these circumstances. OBJECTIVE: Our study aims to provide insights regarding people's psychosocial concerns during the COVID-19 pandemic by leveraging social media data. We aim to study the temporal and linguistic changes in symptomatic mental health and support expressions in the pandemic context. METHODS: We obtained about 60 million Twitter streaming posts originating from the United States from March 24 to May 24, 2020, and compared these with about 40 million posts from a comparable period in 2019 to attribute the effect of COVID-19 on people's social media self-disclosure. Using these data sets, we studied people's self-disclosure on social media in terms of symptomatic mental health concerns and expressions of support. We employed transfer learning classifiers that identified the social media language indicative of mental health outcomes (anxiety, depression, stress, and suicidal ideation) and support (emotional and informational support). We then examined the changes in psychosocial expressions over time and language, comparing the 2020 and 2019 data sets. RESULTS: We found that all of the examined psychosocial expressions have significantly increased during the COVID-19 crisis-mental health symptomatic expressions have increased by about 14%, and support expressions have increased by about 5%, both thematically related to COVID-19. We also observed a steady decline and eventual plateauing in these expressions during the COVID-19 pandemic, which may have been due to habituation or due to supportive policy measures enacted during this period. Our language analyses highlighted that people express concerns that are specific to and contextually related to the COVID-19 crisis. CONCLUSIONS: We studied the psychosocial effects of the COVID-19 crisis by using social media data from 2020, finding that people's mental health symptomatic and support expressions significantly increased during the COVID-19 period as compared to similar data from 2019. However, this effect gradually lessened over time, suggesting that people adapted to the circumstances and their "new normal." Our linguistic analyses revealed that people expressed mental health concerns regarding personal and professional challenges, health care and precautionary measures, and pandemic-related awareness. This study shows the potential to provide insights to mental health care and stakeholders and policy makers in planning and implementing measures to mitigate mental health risks amid the health crisis.


Subject(s)
COVID-19/psychology , Psychology/methods , Social Media , Humans , Non-Randomized Controlled Trials as Topic , SARS-CoV-2/isolation & purification
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