Cross-sectional Time-series Analysis Research Articles

Seasonal Trends in Suicide Attempts-Keywords Related Searches: A Google Trends Analysis.

Suicide is a significant public health concern globally, with its varying rates influenced by numerous factors, including seasonal changes. Online search behaviors, particularly searches related to suicide and mental health, have been proposed as real-time indicators of suicidal ideation in populations. In this study, a cross-sectional time series analysis was conducted, utilizing data on suicide attempts from the Polish Police Headquarters and online search behavior from Google Trends over a decade. Suicide attempt data were analyzed alongside the frequency of Google searches for suicide-related keywords derived from the Polish Corpus of Suicide Notes. A total of 66 keywords were selected for analysis to identify seasonal trends and patterns in search behavior. The study employed linear regression, Seasonal Mann-Kendall tests, and TBATS models to analyze the data. Suicide rates show seasonal patterns, peaking in warmer months. However, keyword searches did not strongly correlate with peak suicide months. This study enhances our understanding of suicide-related search trends and their potential connection to suicide rates. It suggests avenues for more effective prevention efforts and the potential for future algorithms to predict suicide rates and identify at-risk groups.

Trends in opioid toxicities among people with and without opioid use disorder and the impact of the COVID-19 pandemic in Ontario, Canada: A population-based analysis

BackgroundAcross Canada, the COVID-19 pandemic occurred amidst an ongoing drug toxicity crisis. Although elevated rates of substance-related harms have been observed nationally, it remains unknown if the pandemic state of emergency led to disproportionate increases in opioid toxicities among people with opioid use disorder (OUD) compared to those without. MethodsWe conducted a population-based repeated cross-sectional time series analysis of fatal and non-fatal opioid toxicities between January 1, 2014, and December 31, 2021, in Ontario, Canada. We used interventional autoregressive integrated moving average models to examine the impact of the pandemic on monthly rates of opioid toxicities per 100,000 Ontario residents stratified by people with and without OUD. ResultsWe identified 80,296 opioid toxicities of which 53.5 % occurred among people with OUD. Among 52,052 unique individuals, 60.5 % were male and 46.2 % were 25–44 years old. Between January 2014 and December 2021, the rate of opioid toxicities increased from 2.6 to 10.5 per 100,000 (rate ratio [RR]=4.07). The magnitude of this increase differed among people with OUD (0.8 to 7.4 per 100,000; RR=9.35) and without OUD (1.8 to 3.1 per 100,000; RR=1.74). We observed a significant ramp increase in the overall rate of opioid toxicities following the declaration of the pandemic emergency in March 2020 (+0.19 per 100,000 monthly, 95 % CI: 0.029, 0.36, p = 0.021). In a stratified analysis, we found a similar ramp increase among people with OUD (+0.19 per 100,000 monthly, 95 % CI: 0.10, 0.28, p < 0.001); however, this was not observed among people without OUD (p = 0.95). ConclusionsThe rate of opioid toxicities accelerated across Ontario following the pandemic-related state of emergency, with the majority of this increase among people with OUD. The important differences observed among people with OUD compared with those without, highlights the critical need for improved access to harm reduction and treatment interventions among this population.

The logic of sexual violence by state security forces in civil wars

Wartime sexual violence exhibits significant variation both across and within civil conflicts. When explaining this variation, existing scholarly work primarily focuses on rebel groups and overlooks state actors engaged in sexualized civilian victimization. This paper extends the literature by concentrating on states as perpetrators of wartime sexual violence, linking the variation in state-perpetrated sexual violence to battlefield outcomes. It argues that when states suffer from battlefield losses, sexual violence by state security forces is likely to become more prevalent due to changes in motivations at both the command level and the rank-and-file level. Moreover, it suggests that the effect of battle losses on state-perpetrated sexual violence is greater if the states are particularly strong in terms of their military capabilities. Time-series cross-sectional analyses of all armed conflicts between the years 1989 and 2020 provide support for these theoretical expectations, indicating that the effect of battle losses on sexual violence is conditional on states’ military strength. The findings have important implications for the prevention of sexual violence in conflict zones.

The impact of policy and policy communication on COVID-19 vaccination inequalities among Venezuelan refugees and migrants in Colombia: a comparative cross-sectional interrupted time-series analysis

IntroductionEquitable access to vaccines for migrants and refugees is necessary to ensure their right to health and to achieve public health goals of reducing vaccine-preventable illness. Public health policies require...

The “Women’s Representation-Corruption Link” and Environmentalism: A Cross-National Study

Numerous studies suggest a relationship between women’s political representation and improved environmental outcomes. Yet, the contexts in which this holds and the mechanisms through which it comes to be remain understudied. This study proposes that women’s impact on political commitments to environmentalism and policy outcomes are moderated by states’ corruption levels. Although women tend to be more environmental, left-leaning, and risk-averse than men, environments of high-corruption restrain, tokenize, and marginalize women representatives, thereby limiting the impact they may have on environmental governance. Time-series cross-sectional analyses of 58 democracies across 15 years show women’s representation is correlated with better environmental outputs and outcomes, but only when corruption levels are low. These findings help broaden our understanding of the relationship between representation and environmental politics and suggest that the interaction of both integrity and inclusivity in governments holds a key to fighting climate change.

Effects of Political Instability on Private Investment: Empirical Investigation from African Firms

Using data from the World Bank Enterprise Surveys (WBES), our analysis focuses on the effect of perceptions of political instability on private investment at the firm level in Africa. We apply econometric techniques to correct for biases inherent in the data, such as measurement errors, missing observations, and the endogeneity problem. We used time series cross-section analysis employing the two-stage least squares (2SLS) method. Our results show that political instability has a negative and significant impact on business investment, irrespective of location of the firms. However, this effect is insignificant and weak for small firms. Furthermore, we identify a significant impact of administrative constraints, regulatory constraints and infrastructure constraints on investment. These findings highlight the importance of Strengthening political stability in order to stimulate investment, especially in small towns. Putting in place incentives and programmes to encourage employee training can improve business productivity.

Utilisation of and factors associated with non-COVID-19 healthcare services in public facilities amongst cross-border migrants in Thailand, 2019–2022

BackgroundIt is believed that the COVID-19 pandemic might disrupt routine healthcare services. A vulnerable group such as cross-border migrants is of critical concern if the pandemic affects their service utilisation. In this study, we aim to explore the impact of COVID-19 and other related factors on non-COVID-19 service amongst cross-border migrants in Thailand.MethodsWe conducted an ecological time-series cross-sectional analysis using secondary data from 2019 to 2022, focusing on insured and non-insured migrants in a unit of a provincial monthly quarter. We obtained data on registered migrants from the Ministry of Labour and inpatient visits from the Ministry of Public Health (MOPH). Our analysis involved descriptive statistics and a random-effects negative binomial regression, considering variables such as COVID-19 cases, number of hospital beds, registered regions, and COVID-19 waves. We assessed inpatient utilisation number and rate as our primary outcomes.ResultsThe admission numbers for insured and non-insured migrants in all regions increased 1.3–2.1 times after 2019 despite a decrease in the numbers of registered migrants. The utilisation of services for selected communicable and non-communicable diseases and obstetric conditions remained consistent throughout 2019–2022. The admission numbers and rates were not associated with an increase in COVID-19 incidence cases but significantly enlarged as time passed by compared to the pre-COVID-19 period (44.5–77.0% for insured migrants and 15.0–26.4% for non-insured migrants). Greater Bangkok saw the lowest admission rate amongst insured migrants, reflected by the incidence rate ratio of 5.7–27.5 relative to other regions.ConclusionThe admission numbers and rates for non-COVID-19 healthcare services remained stable regardless of COVID-19 incidence. The later pandemic waves (Delta and Omicron variants) were related to an increase in admission numbers and rates, possibly due to disruptions in outpatient care, leading to more severe cases seeking hospitalisation. Lower admission rates in Greater Bangkok may be linked to the fragmentation of the primary care network in major cities and the disintegration of service utilisation data between private facilities and the MOPH. Future research should explore migrant healthcare-seeking behaviour at an individual level, using both quantitative and qualitative methods for deeper insights.

Patterns of early literacy and word reading skill development across the first 6 months of school and reading instruction.

This study described the growth trajectories of 105 children (n = 55 boys) who had just started primary school in New Zealand (NZ). Children were assessed every fourth school week around 1.5 months after starting school, for five sessions on Dynamic Indicators of Basic Early Literacy Skills first sound fluency (FSF), AIMSweb letter sound fluency (LSF), and a newly created NZ word identification fluency (NZWIF-Y1), designed for alignment with beginning reading instruction in NZ. In addition to progress monitoring tasks, children were assessed at school entry and after progress monitoring on literacy-related criterion measures. All three progress monitoring measures were sensitive to growth over the children's first 6 months of school. Cross-sectional time-series analyses indicated that within-child increases in FSF and LSF were associated with increases in NZWIF-Y1, although FSF did not add unique variance when both FSF and LSF were entered as predictors. Furthermore, growth mixture modeling indicated three latent growth trajectories for each indicator (FSF, LSF, NZWIF-Y1, respectively): Class 1-high initial scores and strong growth over time (72.09%, 55.87%, 22.81%); Class 2-lower initial scores and moderate growth over time (19.18%, 29.12%, 54.30%); and Class 3-low initial scores and limited progress over time (8.73%, 15.00%, 22.89%). Criterion measures assessed prior and after progress monitoring were typically associated with latent class membership. Results suggest relative growth in performance on repeated assessment of early literacy and word reading skills in beginning reading instruction distinguishes groups of students with differential skill acquisition. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The effect of European integration on economic redistribution in Central and Eastern Europe

We examine the effects of European integration on economic redistribution in Central and Eastern Europe. While accession to the European Union provided new economic opportunities, it also imposed considerable constraints. Using cross-sectional time-series analysis of 11 post-communist countries between 2004 and 2018, we focus on the impact of trade flows, cohesion policy funds, emigration, remittances, and Economic and Monetary Union membership. We find that emigration and commercial reorientation toward the European Union are associated with greater efforts to alleviate income inequality. In contrast, the adoption of the euro induces lower redistribution. Finally, the receipt of European Union cohesion funds does not affect income differentials. To our knowledge, this is one of the first systematic analyses of how the European Union shapes inequality dynamics in Central and Eastern Europe.

Cheap on Punishment: Examining the Impact of Prison Population Racial Demographics on State-Level Corrections Spending

Research has explored the effects of various state-level characteristics, such as racial composition and economic conditions, on correctional budgetary decisions. However, researchers have yet to consider how the racial makeup of state prison populations themselves may impact subsequent corrections spending decisions. Drawing on work suggesting that people of color are simultaneously over-punished and neglected by criminal justice systems, and utilizing a time-series cross-section analysis of 50 states from 1979 through 2017, we explore differences in state budgetary allocations for correctional expenditures based on the racial demographics of prison populations. We find that the relationship between the Black-to-White incarceration ratio and spending on corrections is curvilinear: once a tipping point of Black-to-White incarceration is reached, spending on corrections decreases. This finding is especially pronounced in Southern and Midwestern states. Overall, our results provide a strong starting point for understanding the ways in which Black Americans are neglected in the incarceration setting.

Commemorating local victims of past atrocities and far-right support over time

Does public remembrance of past atrocities lead to decreased support for far-right parties today? Initiatives commemorating past atrocities aim to make visible the victims and crimes committed against them. This runs counter to revisionist actors who attempt to downplay or deny atrocities and victims. Memorials for victims might complicate such attempts and reduce support for revisionist actors. Yet, little empirical evidence exists on whether that happens. In this study, we examine whether exposure to local memorials that commemorate victims of atrocities reduces support for a revisionist far-right party. Our empirical case is the Stolpersteine ("stumbling stones") memorial in Berlin, Germany. It commemorates victims and survivors of Nazi persecution in front of their last freely chosen place of residence. We employ time-series cross-sectional analyses and a discontinuity design using a panel dataset that matches the location and date of placement of new Stolpersteine with the election results from seven elections (2013 to 2021) at the level of polling station areas. We find that, on average, the presence of Stolpersteine is associated with a 0.96%-point decrease in the far-right vote share in the following election. Our study suggests that local memorials that make past atrocities visible have implications for political behavior in the present.

EPH207 Factors Associated with COVID-19 Infections and Deaths in the Gulf Cooperation Council (GCC) Countries: A Time Series Cross-Section Analysis

COVID19 pandemic has caused significant health and economic burden globally. Compared with high-income nations, prevalence of COVID19 infections and mortality has been lower in GCC countries, but it was higher than MENA region average. There is limited evidence in the literature on pattern and factors associated with COVID19 infections and deaths, especially for six GCC countries. The study aims to investigate this trend and associations. We used world-o-meter online global database for COVID19 infections and deaths, and other databases to capture country-level socio-economic, demographic, and interventional factors linked with COVID19. Trends in monthly COVID19 data were reported via graphs and a negative binomial regression was estimated to determine the association between factors and monthly COVID19 infections and deaths per million population during March 2020 to October 2021. An increasing trend observed in monthly COVID19 cases and deaths up to month 8, followed by a drop and then further increasing trend from month 12 to month 18. For COVID19 infections, negative binomial regression estimates incidence rate ratio (IRR) for ‘stringency index’ as 1.04 (p˂0.001), GDP per capita, IRR=0.99 (p˂0.001), CVD death rate, IRR= 0.99 (p<0.001), diabetes prevalence, IRR= 2.26 (p=0.001), hospital beds per 1,000 population, IRR= 0.002 (p=0.010) and containment health index, IRR= 0.88 (p=0.037). These factors also appeared to be statistically significantly associated with monthly COVID19 deaths per million population. The study contributes to current evidence-base on factors which are potentially associated with COVID19 infections and mortality in six GCC nations. Healthcare policy makers in the region can lessen their COVID19 related health burden by taking appropriate preventing and mitigating measures in relation to factors that have significant associations with the infection and severe disease.

Buprenorphine Utilization and Prescribing Among New Jersey Medicaid Beneficiaries After Adoption of Initiatives Designed to Improve Treatment Access

Buprenorphine is underutilized as a treatment for opioid use disorder (OUD); state policies may improve buprenorphine access and utilization. To assess buprenorphine prescribing trends following New Jersey Medicaid initiatives designed to improve access. This cross-sectional interrupted time series analysis included New Jersey Medicaid beneficiaries who were prescribed buprenorphine and had 12 months continuous Medicaid enrollment, OUD diagnosis, and no Medicare dual eligibility, as well as physician or advanced practitioners who prescribed buprenorphine to Medicaid beneficiaries. The study used Medicaid claims data from 2017 to 2021. Implementation of New Jersey Medicaid initiatives in 2019 that removed prior authorizations, increased reimbursement for office-based OUD treatment, and established regional Centers of Excellence. Rate of buprenorphine receipt per 1000 beneficiaries with OUD; percentage of new buprenorphine episodes lasting at least 180 days; buprenorphine prescribing rate per 1000 Medicaid prescribers, overall and by specialty. Of 101 423 Medicaid beneficiaries (mean [SD] age, 41.0 [11.6] years; 54 726 [54.0%] male; 30 071 [29.6%] Black, 10 143 [10.0%] Hispanic, and 51 238 [50.5%] White), 20 090 filled at least 1 prescription for buprenorphine from 1788 prescribers. Policy implementation was associated with an inflection point in buprenorphine prescribing trend; after implementation, the trend increased by 36%, from 1.29 (95% CI, 1.02-1.56) prescriptions per 1000 beneficiaries with OUD to 1.76 (95% CI, 1.46-2.06) prescriptions per 1000 beneficiaries with OUD. Among beneficiaries with new buprenorphine episodes, the percentage retained for at least 180 days was stable before and after initiatives were implemented. The initiatives were associated with an increase in the growth rate of buprenorphine prescribers (0.43 per 1000 prescribers; 95% CI, 0.34 to 0.51 per 1000 prescribers). Trends were similar across specialties, but increases were most pronounced among primary care and emergency medicine physicians (eg, primary care: 0.42 per 1000 prescribers; 95% CI, 0.32-0.53 per 1000 prescribers). Advanced practitioners accounted for a growing percentage of buprenorphine prescribers, with a monthly increase of 0.42 per 1000 prescribers (95% CI, 0.32-0.52 per 1000 prescribers). A secondary analysis to test for changes associated with non-state-specific secular trends in prescribing found that quarterly trends in buprenorphine prescriptions increased in New Jersey relative to all other states following initiative implementation. In this cross-sectional study of state-level New Jersey Medicaid initiatives designed to expand buprenorphine access, implementation was associated with an upward trend in buprenorphine prescribing and receipt. No change was observed in the percentage of new buprenorphine treatment episodes lasting 180 or more days, indicating that retention remains a challenge. Findings support implementation of similar initiatives but highlight the need for efforts to support long-term retention.

Global trends in antidepressant, atypical antipsychotic, and benzodiazepine use: A cross-sectional analysis of 64 countries.

To describe the trends in use of antidepressants (ADs), atypical antipsychotics (AAPs), and benzodiazepines (BZDs) among high-, middle-, and low-income countries. A cross-sectional time-series analysis by country from July 2014 to December 2019 utilizing IQVIA's Multinational Integrated Data Analysis database was conducted. Population-controlled rates of use were calculated in number of standard units of medications per drug class per population size. The United Nations' 2020 World Economic Situation and Prospects was used to group countries into high-, middle-, and low-income. Percent change in rates of use per drug class was calculated from July 2014 to July 2019. Linear regression analyses were conducted to assess the predictability of percent change in use utilizing a country's baseline rate of use per drug class and economic status as predictor variables. A total of 64 countries were included: 33 high-, 6 middle-, and 25 low-income. Average baseline rates of use for ADs in high-, middle-, and low-income countries were 2.15, 0.35, and 0.38 standard units per population size, respectively. For AAPs, rates were 0.69, 0.15, and 0.13, respectively. For BZDs, rates were 1.66, 1.46, and 0.33, respectively. Average percent changes in use for ADs by economic status were 20%, 69%, and 42%, respectively. For AAPs, they were 27%, 78%, and 69%, respectively. For BZDs, they were -13%, 4%, and -5%, respectively. Some associations were found demonstrating that as a country's economic status increases, percent change of AD (p = 0.916), AAP (p = 0.23), and BZD (p = 0.027) use decreases. Similarly, as baseline rate of use for ADs and AAPs increases, percent change in use decreases with p-values of 0.026 and 0.054, respectively. For BZDs, as baseline rate of use increases, percent change in use increases (p = 0.038). High-income countries have a higher rate of treatment utilization compared to low- and middle-income countries (LMICs) with treatment utilization increasing in all countries of interest.

Association of physician malpractice claims rates with admissions for low-risk chest pain

BackgroundChest pain accounts for 5% of all emergency department visits and accounts for the highest malpractice payout against emergency physicians. To clarify the impact of defensive medicine, we assessed whether admission rates of low-risk chest pain patients are associated with malpractice claims rates. MethodsA cross-sectional time-series analysis of state-year level malpractice claims rates, admission rates for low-risk chest pain (LRCP; requiring ED physician discretion), and admission rates for acute myocardial infarction (AMI; requiring minimal physician judgment for admission, used as a control) from 2008 to 2017 was performed. Admission rates were derived from Optum's deidentified Clinformatics Data Mart Database. LRCP visits were defined by primary ICD-9 or ICD-10 codes of 786.5, R07.9, or R07.89; length of stay of 2 or fewer days; and no previous major cardiac diagnosis and AMI visits with ICD-9 or ICD-10 codes 410, I21.3, or I121.9. Malpractice claims rates (MPCRs) were derived from the National Practitioner Database (NPD). The association between state-year level MPCR and admission rates for LRCP and AMI was estimated using state fixed-effects models. Standardized costs were inflation adjusted and are expressed in US dollar rate as of 2019. ResultsThere were 40,482,813 ED visits during the 10-year study period, of which 2,275,757 (5.6%) were for chest pain, and 1,163,881 met LRCP criteria. Mean age of LRCP patients was 67.8 years, 60.9% were female, and 16.6% were hospitalized, at a mean cost of $17,120. During the same period, 75,266 (0.2%) visits were for AMI, with 87% admitted. The MPCR by state-year varied widely, from 2.6 to 8.6 claims per 100,000 population. A state fixed-effects model showed that an additional physician malpractice claim per 100,000 population was associated with a 3.66% (95% CI 2.02%–5.30%) increase in the admission rate of LRCP. An analogous model showed no association between MPCR and admission rates for AMI (−1.52%, 95% CI −4.06% to 1.02%). ConclusionHigher MPCRs are associated with increased admission rates for LRCP, at substantial cost, which may be attributable to defensive medicine in the ED.

Prescribing of low-dose rivaroxaban in patients with atherosclerotic cardiovascular disease in the United Kingdom and the Netherlands.

Low-dose rivaroxaban has been indicated for the management of atherosclerotic cardiovascular disease (ASCVD) after recent (2019-2020) updates to European guidelines. We aimed to describe prescription trends of low-dose rivaroxaban in ASCVD patients over the period 2015-2022 in two European countries, to compare the trends before and after guideline changes, and to determine the characteristics of users. In a cross-sectional interrupted time series analysis, utilization of low-dose rivaroxaban (2.5 mg, twice daily) was measured in Clinical Practice Research Datalink Aurum (United Kingdom [UK]) and the PHARMO Database Network (the Netherlands) from 1 January 2015 to 28 February 2022 in patients with an ASCVD diagnosis. Incidence rates (IRs) and incidence rate ratios (IRRs) of new use (within 182 days) compared to the reference period, 2015-2018, were calculated. Age, sex and comorbidities of users were compared to those of nonusers. In the UK, from 721 271 eligible subjects the IR of new use of low-dose rivaroxaban in the period 2015-2018, before guideline changes, was 12.4 per 100 000 person-years and after guideline changes in 2020-2022 was 124.0 (IRR 10.0, 95% confidence interval [CI] 8.5, 11.8). In the Netherlands from 394 851 subjects, the IR in 2015-2018 was 2.4 per 100 000 person-years and in 2020 was 16.3 (IRR 6.7, 95% CI 4.0, 11.4). Users were younger (UK mean difference [MD] -6.1years, Netherlands -2.4years; P< .05) and more likely to be male (UK difference 11.5%, Netherlands 13.4%; P< .001) than nonusers. There was a statistically significant increase in the use of low-dose rivaroxaban for the management of ASCVD after guideline changes in the UK and the Netherlands. There were international differences, but low-dose rivaroxaban has not been put into widespread practice.

Assessment of Low-Level Air Pollution and Cardiovascular Incidence in Gdansk, Poland: Time-Series Cross-Sectional Analysis.

(1) Background: More than 1.8 million people in the European Union die every year as a result of CVD, accounting for 36% of all deaths with a large proportion being premature (before the age of 65). There are more than 300 different risk factors of CVD, known and air pollution is one of them. The aim of this study was to investigate whether daily cardiovascular mortality was associated with air pollutants and meteorological conditions in an urban environment with a low level of air pollution. (2) Methods: Data on daily incidence of strokes and myocardial infarctions in the city of Gdansk were obtained from the National Health Fund (NHF) and covered the period from 1 January 2014 to 31 December 2018. Data on the level of pollution, i.e., SO2, NO, NO2, NOx, CO, PM10, PM2.5, CO2, O3 and meteorological conditions came from the foundation: Agency of Regional Air Quality Monitoring in the Gdańsk metropolitan area (ARMAG). Using these data, we calculated mean values with standard deviation (SD) and derived the minimum and maximum values and interquartile range (IQR). Time series regression with Poisson distribution was used in statistical analysis. (4) Results: Stroke incidence is significantly affected by an increase in concentrations of NO, NO2 and NOx with RRs equal to 1.019 (95%CI: 1.001-1.036), 1.036 (95%CI: 1.008-1.064) and 1.017 (95%CI: 1.000-1.034) for every increase in IQR by 14.12, 14.62 and 22.62 μg/m3, respectively. Similarly, myocardial infarction incidence is significantly affected by an increase in concentrations of NO, NO2 and NOx with RRs equal to 1.030 (95%CI: 1.011-1.048), 1.053 (95%CI: 1.024-1.082) and 1.027 (95%CI: 1.010-1.045) for every increase in IQR by 14.12, 14.62 and 22.62 μg/m3, respectively. Both PM10 and PM2.5 were positively associated with myocardial infarction incidence. (5) Conclusions: In this time-series cross-sectional study, we found strong evidence that support the hypothesis that transient elevations in ambient PM2.5, PM10, NO2, SO2 and CO are associated with higher relative risk of ischemic stroke and myocardial infarction incidents.

Estimated impact of the COVID-19 pandemic on the prevalence and treatment of depressive symptoms in Peru: an interrupted time series analysis in 2014–2021

PurposeThe COVID-19 pandemic increased the burden of mental disorders worldwide. Peru has been one of the countries most affected by COVID-19, however, studies evaluating the medium and long-term consequences of the pandemic on Peruvians’ mental health are recent and represent a new field of study in proliferation. We aimed to estimate the impact of the COVID-19 pandemic on the prevalence and treatment of depressive symptoms using nationally representative surveys in Peru.MethodsOur study is an analysis of secondary data. We carried out a time series cross-sectional analysis based on the National Demographic and Health Survey of Peru, collected using a complex sampling design. The Patient Health Questionnaire-9 was used to measure mild (5–9 points), moderate (10–14 points), and severe (15 points or more) depressive symptoms. The participants were men and women aged 15 years and older, living in urban and rural areas of all regions of Peru. The main statistical analysis used segmented regression with Newey-West standard errors, taking into account that each year of the evaluation was divided into four measures (quarter measure).ResultsWe included 259,516 participants. An average quarterly increase of 0.17% (95% CI 0.03–0.32%) in the prevalence of moderate depressive symptoms was identified after the onset of the COVID-19 pandemic (approximately an increase of 1583 new cases of moderate depressive symptoms by each quarter). The percentage of cases treated for mild depressive symptoms increased quarterly by an average of 0.46% (95% CI 0.20–0.71%) after the onset of the COVID-19 pandemic (approximately an increase of 1242 new cases treated for mild depressive symptoms by each quarter).ConclusionIn Peru, increases in the prevalence of moderate depressive symptoms and the proportion of cases treated with mild depressive symptoms were found after the COVID-19 pandemic. Therefore, this study is a precedent for future research assessing the prevalence of depressive symptoms and the proportion of cases receiving treatment during the pandemic and post-pandemic years.

Economic development, corruption, and income inequality: The role of the informal sector

This article investigates how the relationship between economic development and income inequality is conditioned by corruption and the informal sector. While corruption has traditionally been believed to worsen inequality through resource concentration, this study suggests that it can also lead to the opposite through the informal sector. In countries with a high level of corruption or a large informal sector, individuals can bypass regulations and barriers by offering bribes or participating in the informal economy; this allows the benefits of economic development to be widely distributed, thereby reducing inequality. The reverse is true when corruption is low or the informal sector is small. However, at low levels of economic development, an increase in informal economy or corruption alone would not lead to a more egalitarian distribution without an economic expansion. The arguments are supported with a time-series cross-sectional analysis of 127 countries from 1964 to 2007. This study contributes to the literature by clarifying the relationship between corruption and the informal sector and how they affect inequality jointly with economic development.

Effects of corruption and income inequality on the reported number of COVID-19 cases and deaths: Evidence from a time series cross-sectional data analysis.

Corruption-income inequality nexus is likely to affect the healthcare services, which in turn affect a country's ability to suppress an epidemic. Widespread corruption in public sectors may influence the data inventory practices to control the recording and sharing of official statistics to avoid political disturbance or social problems caused by an epidemic. This empirical study examines the effects of income inequality, data inventory, and universal healthcare coverage on cross-country variation in reported numbers of COVID-19 cases and deaths in the presence of corruption in public sectors. Daily numbers of COVID-19 cases and deaths of selected 29 countries are integrated for the first 120 days of the epidemic in each country. COVID-19 dataset is then integrated with a dataset of different indices. Fixed effect panel model is applied to explore the effects of corruption perception, income inequality, open data inventory practice, and universal health coverage on the daily numbers of COVID-19 cases and deaths per million. Income inequality, corruption perception and open data inventory are found to significantly affect the number of confirmed cases and deaths. Countries with alarming income inequality are found to report 39.89 more COVID-19 cases per million, on average. Under a lower level of corruption, countries with lower level of open data inventory are expected to report 74.31 more COVID-19 cases but 1.43 less deaths per million. Given a higher level of corruption, countries with lower level of open data inventory are expected to report lower number of COVID-19 cases and deaths. Corruption demonstrates a significant influence on the size of the epidemic in terms of the number of COVID-19 cases and deaths. A country with higher level of corruption in public sector along with lower levels of open data inventory is expected to report lower number of COVID-19 cases and deaths.