Gallbladder cancer (GBC) mortality in Chile is among the highest worldwide. In 2006, the Chilean government launched a programme guaranteeing access to gallbladder surgery (cholecystectomy) for patients aged 35-49 years. We evaluated the impact of this programme on digestive cancer mortality. After conducting an interrupted time series analysis of hospitalisation and mortality data from 2002 to 2018 publicly available from the Chilean Department of Health Statistics and Information, we calculated the change in the proportion of individuals without gallbladder since 10 years. We then estimated age, gender, region, and calendar-year standardised mortality ratios (SMRs) as a function of the change in the proportion of individuals without gallbladder. The cholecystectomy rate increased by 45 operations per 100,000 persons per year (95%CI 19-72) after the introduction of the health programme. Each 1% increase in the proportion of individuals without gallbladder since 10 years was associated with a 0.73% decrease in GBC mortality (95% CI -1.05% to -0.38%), but the negative correlation was limited to women, southern Chile and age over 60. We also found decreasing mortality rates for extrahepatic bile duct, liver, oesophageal and stomach cancer with increasing proportions of individuals without gallbladder. To conclude, 12 years after its inception, the Chilean cholecystectomy programme has markedly and heterogeneously changed cholecystectomy rates. Results based on aggregate data indicate a negative correlation between the proportion of individuals without gallbladder and mortality due to gallbladder and other digestive cancers, which requires validation using individual-level longitudinal data to reduce the potential impact of ecological bias.

BACKGROUND: Postpartum depression (PPD) has received widespread attention. Shenzhen has been running a large-scale program for PPD since 2013. The program requires mothers to self-assess when applying information technology to PPD screening beginning in 2021. The purpose of this study was to conduct a longitudinal analysis of the impact of mHealth apps on the health-seeking behaviors of PPD patients.
METHODS: Longitudinal data from districts in the Shenzhen Maternal and Child Health Management Information System (MCHMIS) for ten years was used in this study. Referral success rate (RSR, successful referrals to designated hospitals as a percentage of needed referrals) was used to assess health-seeking behavior. Trend χ2 tests were used to assess the overall trend of change after the implementation of mHealth in ten districts in Shenzhen. Interrupted Time Series Analysis (ITSA) was employed to assess the role of the mHealth app in changing patient health-seeking behaviors.
RESULTS: For the results of the trend χ2 tests, the ten districts of Shenzhen showed an upward trend. For the ITSA results, different results were shown between districts. Nanshan district, Longhua district, and Longgang district all demonstrated an upward trend in the first-year application of the mHealth app. Nanshan district and Longgang district both exhibited an upward trend in terms of sustained effects.
CONCLUSIONS: There is a difference in the performance of the mHealth app across the ten districts. The results show that the three districts with better health resource allocation, Nanshan, Longgang, and Longhua districts, demonstrated more significant mHealth app improvements. The mHealth app\'s functions, management systems, and health resource allocation may be potential factors in the results. This suggests that when leveraging mHealth applications, the first step is to focus on macro-level area resource allocation measures. Secondly, there should be effective process design and strict regulatory measures. Finally, there should also be appropriate means of publicity.

UNASSIGNED: The emergency response to the COVID-19 pandemic may disrupt hospital management activities of antimicrobial resistance (AMR). This study aimed to determine the changing AMR trend over the period in China when stringent COVID-19 response measures were implemented.
UNASSIGNED: This retrospective study was conducted in a designated hospital for COVID-19 patients in Guangzhou, China from April 2018 to September 2021. The prevalence of 13 antimicrobial-resistant bacteria was compared before and after the COVID-19 responses through Chi-square tests. Interrupted time series (ITS) models on the weekly prevalence of AMR were established to determine the changing trend. Controlled ITS models were performed to compare the differences between subgroups.
UNASSIGNED: A total of 10,134 isolates over 1,265 days were collected. And antimicrobial-resistant strains presented in 38.6% of the testing isolates. The weekly AMR prevalence decreased by 0.29 percentage point (95% CI [0.05-0.80]) after antimicrobial stewardship (AMS) policy, despite an increase in the prevalence of penicillin-resistant Streptococcus pneumoniae (from 0/43 to 15/43, p < 0.001), carbapenem-resistant Escherichia coli (from 20/1254 to 41/1184, p = 0.005), and carbapenem-resistant Klebsiella pneumoniae (from 93/889 to 114/828, p = 0.042). And the changing trend did not vary by gender (male vs. female), age (<65 vs. ≥65 years), service setting (outpatient vs. inpatient), care unit (ICU vs. non-ICU), the primary site of infection (Lung vs. others), and Gram type of bacteria (positive vs. negative).
UNASSIGNED: The response to COVID-19 did not lead to an increase in overall AMR; however, it appears that management strategy on the prudent use of antimicrobials likely contributed to a sizable long-term drop. The frequency of several multidrug-resistant bacteria continues to increase after the COVID-19 epidemic. It is crucial to continue to monitor AMR when COVID-19 cases have surged in China after the relaxation of restriction measures.

BACKGROUND: The emergence of COVID-19 precipitated containment policies (e.g., lockdowns, school closures, etc.). These policies disrupted healthcare, potentially eroding gains for Sustainable Development Goals including for neonatal mortality. Our analysis aimed to evaluate indirect effects of COVID-19 containment policies on neonatal admissions and mortality in 67 neonatal units across Kenya, Malawi, Nigeria, and Tanzania between January 2019 and December 2021.
METHODS: The Oxford Stringency Index was applied to quantify COVID-19 policy stringency over time for Kenya, Malawi, Nigeria, and Tanzania. Stringency increased markedly between March and April 2020 for these four countries (although less so in Tanzania), therefore defining the point of interruption. We used March as the primary interruption month, with April for sensitivity analysis. Additional sensitivity analysis excluded data for March and April 2020, modelled the index as a continuous exposure, and examined models for each country. To evaluate changes in neonatal admissions and mortality based on this interruption period, a mixed effects segmented regression was applied. The unit of analysis was the neonatal unit (n = 67), with a total of 266,741 neonatal admissions (January 2019 to December 2021).
RESULTS: Admission to neonatal units decreased by 15% overall from February to March 2020, with half of the 67 neonatal units showing a decline in admissions. Of the 34 neonatal units with a decline in admissions, 19 (28%) had a significant decrease of ≥ 20%. The month-to-month decrease in admissions was approximately 2% on average from March 2020 to December 2021. Despite the decline in admissions, we found no significant changes in overall inpatient neonatal mortality. The three sensitivity analyses provided consistent findings.
CONCLUSIONS: COVID-19 containment measures had an impact on neonatal admissions, but no significant change in overall inpatient neonatal mortality was detected. Additional qualitative research in these facilities has explored possible reasons. Strengthening healthcare systems to endure unexpected events, such as pandemics, is critical in continuing progress towards achieving Sustainable Development Goals, including reducing neonatal deaths to less than 12 per 1000 live births by 2030.

UNASSIGNED: An increasing number of countries have or are considering legalizing cannabis. One concern is that legalization of cannabis will result in increased cannabis use and in turn a higher prevalence of anxiety disorders. We examined changes in emergency department (ED) visits for anxiety disorders with cannabis involvement in Ontario, over a period that involved medical and non-medical cannabis legalization.
UNASSIGNED: This repeated cross-sectional population-based study identified all ED visits for anxiety disorders from residents of Ontario, Canada aged 10-105 between 2008 and 2022 (n = 15.7 million individuals). We used interrupted time series analyses to examine immediate and gradual changes in cannabis-involvement and alcohol-involvement (control condition) over four policy periods: medical cannabis legalization (January 2008-November 2015), expanded medical access (December 2015-September 2018), non-medical cannabis legalization with restrictions (October 2018-February 2020), and commercialization which overlapped with the COVID-19 pandemic (March 2020-December 2022). Poisson models were used to generate incidence rate ratios with 95% confidence intervals.
UNASSIGNED: Over the 14-year study, there were 438,700 individuals with one or more ED visits for anxiety disorders of which 3880 (0.89%) individuals had cannabis involvement and 6329 (1.45%) individuals had alcohol involvement. During the commercialization/COVID-19 period monthly rates of anxiety disorders with cannabis-involvement were 156% higher (0.11 vs 0.29 per 100,000 individuals) relative to the pre-legalization period, compared to a 27% increase for alcohol-involvement (0.27 vs 0.35 per 1100,000 individuals). Rates of anxiety ED visits with cannabis involvement per 100,000 individuals increased gradually over the study period with no immediate or gradual changes after expanded medical access, legalization with restrictions or commercialization/COVID-19. However, during the commercialization/COVID-19 period there were large declines in total anxiety disorder ED visits and anxiety disorder ED visits with alcohol-involvement. Consequently, during this period there was an immediate 31.4% relative increase in the proportion of anxiety visits with cannabis-involvement (incidence rate ratio [IRR], 1.31; 95% CI 1.05-1.65).
UNASSIGNED: We found large relative increases in anxiety disorder ED visits with cannabis involvement over a 14-year period involving medical and non-medical cannabis legalization. These findings may reflect increasing anxiety disorder problems from cannabis use, increasing self-medication of anxiety disorders with cannabis use, or both. The proportion of anxiety ED visits with cannabis involvement increased during the final period of the study but could have been the results of the market commercialization, COVID-19 or both and ongoing monitoring is indicated.
UNASSIGNED: Canadian Institutes of Health Research (grant #452360).

When studying the impact of policy interventions or natural experiments on air pollution, such as new environmental policies and opening or closing an industrial facility, careful statistical analysis is needed to separate causal changes from other confounding factors. Using COVID-19 lockdowns as a case-study, we present a comprehensive framework for estimating and validating causal changes from such perturbations. We propose using flexible machine learning-based comparative interrupted time series (CITS) models for estimating such a causal effect. We outline the assumptions required to identify causal effects, showing that many common methods rely on strong assumptions that are relaxed by machine learning models. For empirical validation, we also propose a simple diagnostic criterion, guarding against false effects in baseline years when there was no intervention. The framework is applied to study the impact of COVID-19 lockdowns on NO2 in the eastern US. The machine learning approaches guard against false effects better than common methods and suggest decreases in NO2 in Boston, New York City, Baltimore, and Washington D.C. The study showcases the importance of our validation framework in selecting a suitable method and the utility of a machine learning based CITS model for studying causal changes in air pollution time series.

BACKGROUND: We performed a nationwide analysis to evaluate the impact of the early coronavirus disease 2019 (COVID-19) pandemic on emergency department (ED) visits by adult cancer patients having COVID-like symptoms.
METHODS: We analyzed the National Emergency Department Information System (NEDIS) data on ED visits by adult cancer patients who presented with chief complaints of fever or respiratory symptoms (FRS) indicative of COVID-19, from 2016 to 2020. An interrupted time series analysis with a quasi-Poisson regression model was performed, adjusting for seasonality and time, to evaluate whether underlying trends for monthly ED visits and the in-hospital mortality rate (%) per month changed with the pandemic among these patients. We also estimated the adjusted odds ratio (aOR) of in-hospital deaths among cancer patients using multivariable logistic regression analysis.
RESULTS: ED visits by cancer patients with FRS decreased during the COVID-19 pandemic (relative risk [RR] with 95% confidence interval [CI]: slope change, 0.99 [0.98-1.00] and step change, 0.84 [0.76-0.92]). However, the in-hospital mortality rate (%) for these patients was increased (slope change, 1.14 [1.04-1.25] and step change, 0.99 [0.98-1.01]). Factors such as urgent triage status, ambulance use, and treatment in hospitals with fewer than 300 staffed beds significantly contributed to increased aOR of in-hospital deaths during the COVID-19 pandemic compared to the pre-pandemic period.
CONCLUSIONS: Further studies are needed to highlight the importance of ED service preparation in planning and managing resources for cancer patients during future pandemics.

Objective: This study sought to assess the impact of a novel electronic audit and feedback (e-A&F) system on patient outcomes. Methods: The e-A&F intervention was implemented in a tertiary hospital and involved near real-time feedback via web-based dashboards. We used a segmented regression analysis of interrupted time series. We modelled the pre-post change in outcomes for the (1) announcement of this priority list, and (2) implementation of the e-A&F intervention to have affected patient outcomes. Results: Across the study period there were 222,792 episodes of inpatient care, of which 13,904 episodes were found to contain one or more HACs, a risk of 6.24%. From the point of the first intervention until the end of the study the overall risk of a HAC reduced from 8.57% to 4.12% - a 51.93% reduction. Of this reduction the proportion attributed to each of these interventions was found to be 29.99% for the announcement of the priority list and 21.93% for the implementation of the e-A&F intervention. Discussion: Our findings lend evidence to a mechanism that the announcement of a measurement framework, at a national level, can lead to local strategies, such as e-A&F, that lead to significant continued improvements over time.

BACKGROUND: The Canadian Cannabis Act (CCA, implemented in October 2018) and the COVID-19 pandemic (April 2020) might have contributed to cannabis-related harms in Québec, known for its stringent cannabis legal framework. We explored changes in incidence rates of cannabis-related disorders (CRD) diagnoses associated with these events in Québec.
METHODS: We utilized linked administrative health data to identify individuals aged 15 year+ newly diagnosed with CRD during hospitalizations, emergency, and outpatients clinics across Québec, from January 2010 and March 2022 (147 months). Interrupted time-series analyses (ITSA) assessed differences (as percentage changes) in sex- and age-standardized, and sex-stratified, monthly incidence rates (per 100,000 population) attributed to the CCA and the COVID-19 pandemic, compared to counterfactual scenarios where pre-events trends would continue unchanged.
RESULTS: The overall monthly mean rates of incident diagnoses nearly doubled from the pre-CCA period (1.56 per 100,000 population) to the COVID-19 pandemic period (3.02 per 100,000 population). ITSA revealed no statistically significant level or slope changes between adjacent study periods, except for a decrease in the slope of incidence rates among males by 1.84 % (95 % CI -3.41 to -0.24) during the COVID-19 pandemic compared to the post-CCA period. During the post-CCA period, the trends of incidence rates in the general and male populations grew significantly by 1.22 % (95 % CI 0.08 to 2.35) and 1.44 % (0.04 to 2.84) per month, respectively. Similarly significant increases were observed for the general and female populations during the COVID-19 pandemic, with monthly rates rising by 1.43 % (95 % CI 0.75 to 2.12) and 1.75 % (95 % CI 0.13 to 3.37), respectively. These increases more than doubled pre-CCA rates.
CONCLUSIONS: The incidence rates of CRD diagnoses across Québec appears to have increased following the implementation of the CCA and during the COVID-19 pandemic. Our findings echo public health concerns regarding potential cannabis-related harms and are consistent with previous Canadian studies.

UNASSIGNED: Daily, approximately 3,400 traffic-related deaths occur globally, with over 90% concentrated in low and middle-income countries (LMICs). Notably, Rwanda has one of the highest road traffic death rates in the world (29.7 per 100,000 people) and is the first low-income country to implement a national Automated Speed Enforcement (ASE) policy. The primary goal of this study is to evaluate the effectiveness of ASE cameras in reducing the primary outcome of road traffic deaths and secondary outcomes of serious injury crashes and fatal crashes.
UNASSIGNED: The study used data on road traffic deaths, and serious injury and fatal crashes collected by the Rwanda National Police between 2010 and 2022. Interrupted time series (ITS) models were fit to quantify the association between ASE and change in road traffic crash outcomes, adjusted for COVID-19-related variables (such as the start of the pandemic, the closure of schools and bars), along with exposure variables (such as GDP and population), and other concurrent road safety measures (such as road safety campaigns).
UNASSIGNED: The ITS models show that the implementation of ASE cameras significantly reduced road traffic deaths, serious injury crashes, and fatal crashes at the provincial level. For instance, the implementation of ASE cameras in the whole of Rwanda in April 2021 was significantly associated with a 0.14 (95% CI [0.072, 0.212]) reduction in monthly death incidence, equating to a 38.16% monthly decrease compared to the period before their installation (January 2010-March 2021).
UNASSIGNED: This study emphasizes the significant association of ASE in Rwanda with improved road traffic crash outcomes, a result that may inform road safety policy in other LMICs. Rwanda has become the first low-income country to implement nationwide scaling of ASE in Africa, paving the way for the generation of valuable evidence on speed-related interventions. In addition to new knowledge generation, African road safety research efforts like this one are opportunities to grow academic and law enforcement cooperations while improving data systems and sources for future research benefits.