Lancet Regional Health-Americas最新文献

{"title":"Hospitalizations for all-cause pediatric acute respiratory diseases in Alberta, Canada, before, during, and after the COVID-19 pandemic: a population-level retrospective cohort study from 2010 to 2024","authors":"Christine D. Lukac ,&nbsp;Brett Simms ,&nbsp;Grace P.S. Kwong ,&nbsp;Jessalyn K. Holodinsky ,&nbsp;David W. Johnson ,&nbsp;James D. Kellner","doi":"10.1016/j.lana.2025.101024","DOIUrl":"10.1016/j.lana.2025.101024","url":null,"abstract":"<div><h3>Background</h3><div>This population-level retrospective cohort study measured seasonal patterns of pediatric hospitalizations, pediatric intensive care unit (PICU) admissions, and average age of children diagnosed with acute respiratory diseases (ARD) during pre-pandemic, COVID-19 pandemic, and late/post-pandemic periods.</div></div><div><h3>Methods</h3><div>From September 2010 through August 2024, all hospitalizations for ARD among children &lt;18 years old were identified from the provincial Discharge Abstract Database, in Alberta, Canada. Seasonal autoregressive integrated moving average (SARIMA) models were developed based on pre-pandemic trends and predicted expected weekly outcomes with 95% confidence intervals (95% CI) from March 2020 onward. Observed and expected outcomes with 95% CI were compared to measure impacts during peak seasons.</div></div><div><h3>Findings</h3><div>There were 52,839 ARD hospitalizations: 16,003 (30.29%) bronchiolitis, 7958 (15.06%) influenza-like illness, 14,366 (27.19%) pneumonia, 2989 (5.66%) croup, 10,266 (19.43%) asthma exacerbation, and 1257 (2.38%) COVID-19. Further, 4433 (8.39%) hospitalizations included a PICU admission. During the pre-pandemic period, hospitalizations for ARD had a biennial pattern, where the peak incidence was highest every other winter season. During the pandemic and late/post-pandemic periods, the average weekly incidence of hospitalization for ARD/100,000 children decreased 91.25% during winter 2020–2021 (1.03 observed vs. 11.81 [95% CI 7.30, 16.33] expected), increased 47.98% during winter 2022–2023 (18.06 observed vs. 12.20 [95% CI 7.06, 17.34] expected), and returned near pre-pandemic incidence during winter 2023–2024 (12.87 observed vs. 11.87 [95% CI 6.08, 17.67] expected) compared with incidence predicted by the SARIMA model. During winter 2022–2023 when hospitalizations surged, there was no significant change in the average weekly incidence of PICU admissions for ARD/100,000 children (2.07 observed vs. 1.26 [95% CI 0.26, 2.27] expected), nor percent PICU admissions (10.21% observed vs. 10.11% [95% CI 5.50, 14.73] expected), nor in average age (31.95 months observed vs. 34.20 months [95% CI 25.89, 42.52] expected).</div></div><div><h3>Interpretation</h3><div>Hospitalizations for pediatric ARD decreased dramatically during winter 2020–2021, surged during winter 2022–2023, and returned near pre-pandemic incidence during winter 2023–2024. There was no lasting change in PICU admissions nor average age. Ongoing surveillance will describe the evolving seasonal pattern of ARD during the post-pandemic period.</div></div><div><h3>Funding</h3><div>None.</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"44 ","pages":"Article 101024"},"PeriodicalIF":7.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quality of care in Colombian women with early-onset breast cancer in two time periods: findings from a nationwide administrative registry cohort","authors":"Ana Maria Valbuena-Garcia ,&nbsp;Silvia Juliana Trujillo-Cáceres ,&nbsp;Juliana Alexandra Hernández Vargas ,&nbsp;Sandra Diaz ,&nbsp;Lizbeth Acuña ,&nbsp;Sandra Perdomo ,&nbsp;Marion Piñeros","doi":"10.1016/j.lana.2025.101018","DOIUrl":"10.1016/j.lana.2025.101018","url":null,"abstract":"<div><h3>Background</h3><div>Early-onset breast cancer (EOBC) refers to breast cancer diagnosed in women aged 18–45 years, being in many cases associated with hereditary breast cancer syndromes, diagnosed at more advanced stages and worse prognosis. In this paper, we sought to describe the main characteristics of EOBC and quality of care within the framework of the national health system in Colombia.</div></div><div><h3>Methods</h3><div>Cross-sectional study. We used a national administrative cancer registry, including women diagnosed with EOBC between 2017 and 2022. Demographic and clinical characteristics, as well as quality healthcare indicators, were compared (numbers and percentages) over two periods (2017–2019, 2020–2022), stratified by health insurance scheme.</div></div><div><h3>Findings</h3><div>7621 women with incident EOBC were included, constituting 19.4% (7621/39,238) of all breast cancers reported in the study period. The mean age was 39.2 (SD 5.2). Most of the cases (23% [1753/7621]) were diagnosed at stage IIA. Systemic therapy was the most frequent first treatment. When comparing both periods, the main areas of improvement were related to breast-conserving surgery for early stages (from 60.3% [459/761] to 68.3% [699/1024]), access to palliative care for metastatic cancer (from 29.5% [59/199] to 54.9% [101/184]), and reduction of waiting times. The time from collecting biopsy samples to receiving results showed the biggest improvement between periods (from a mean of 24.5 to 5.0 days). However, delays in initiating treatment persist, with an average of over two months.</div></div><div><h3>Interpretation</h3><div>While the quality of breast cancer care in women with EOBC has improved in recent years in Colombia, mainly due to better access to specific technologies and treatments, there are important challenges regarding early detection and health services delays that require corrective measures.</div></div><div><h3>Funding</h3><div>Work at the IARC/WHO was supported by regular budget funding.</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101018"},"PeriodicalIF":7.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning to predict dementia for American Indian and Alaska native peoples: a retrospective cohort study","authors":"Kayleen Ports ,&nbsp;Jiahui Dai ,&nbsp;Kyle Conniff ,&nbsp;Maria M. Corrada ,&nbsp;Spero M. Manson ,&nbsp;Joan O’Connell ,&nbsp;Luohua Jiang","doi":"10.1016/j.lana.2025.101013","DOIUrl":"10.1016/j.lana.2025.101013","url":null,"abstract":"<div><h3>Background</h3><div>Dementia is an increasing concern among American Indian and Alaska Native (AI/AN) communities, yet machine learning models utilizing electronic health record (EHR) data have not been developed or validated for this population. This study aimed to develop a two-year dementia risk prediction model for AI/AN individuals actively using Indian Health Service (IHS) and Tribal health services.</div></div><div><h3>Methods</h3><div>Seven years of data were obtained from the IHS National Data Warehouse and related EHR databases and divided into a five-year baseline period (FY2007–2011) and a two-year dementia prediction period (FY2012–2013). Four algorithms were assessed: logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme Gradient Boosting (XGBoost). Dementia Risk Score (DRS)-based and extended models were developed for each algorithm, with performance evaluated by the area under the receiver operating characteristic curve (AUC).</div></div><div><h3>Findings</h3><div>The study cohort included 17,398 AI/AN adults aged ≥ 65 years who were dementia-free at baseline, of whom 59.8% were female. Over the two-year follow-up, 611 individuals (3.5%) were diagnosed with incident dementia. Extended models for logistic regression, LASSO, and XGBoost performed comparably: AUCs (95% CI) of 0.83 (0.79, 0.86), 0.83 (0.79, 0.86), and 0.82 (0.79, 0.86). These top-performing models shared 12 of the 15 highest-ranked predictors, with novel predictors including service utilization.</div></div><div><h3>Interpretation</h3><div>Machine learning algorithms utilizing EHR data can effectively predict two-year dementia risk among AI/AN older adults. These models could aid IHS and Tribal health clinicians in identifying high-risk individuals, facilitating timely interventions and improved care coordination.</div></div><div><h3>Funding</h3><div><span>NIH</span>.</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101013"},"PeriodicalIF":7.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of conditional cash transfer programs on health outcomes in Argentina: a retrospective, observational analysis based on MICS 2019/2020","authors":"Zlatko Nikoloski ,&nbsp;Maria Elisa Zapata ,&nbsp;Elias Mossialos","doi":"10.1016/j.lana.2025.101011","DOIUrl":"10.1016/j.lana.2025.101011","url":null,"abstract":"<div><h3>Background</h3><div>Conditional cash transfers (CCTs) are widely used to combat intergenerational poverty and to invest in human capital. Argentina introduced its own CCT program AUH (<em>Asignación Universal por Hijo</em>) in 2009. The aim of this research was to assess the relationship between the AUH program and key indicators: healthcare use, nutritional indicators (among children under five years), and high school enrollment.</div></div><div><h3>Methods</h3><div>We utilized data from the Multiple Indicators Cluster Survey (MICS) conducted in Argentina between late 2019 and early 2020. Specifically, we employed different matching techniques to estimate the relationship between AUH and healthcare utilization and high school enrolment. Additionally, we assessed the program's importance in improving nutrition outcomes among children under five years.</div></div><div><h3>Findings</h3><div>Our analysis reveals that the AUH program has not significantly increased healthcare utilization among affiliated children. When accounting for program heterogeneity, the impact of the program was found to be consistent across boys and girls, and across children of different ages, although we found evidence of increased healthcare utilization among adolescents. In addition, there was no statistically significant evidence for a link between program affiliation and reduction in stunting and wasting among children under five years. Furthermore, the program has led to increased high school enrolment among boys, consistent with established findings.</div></div><div><h3>Interpretation</h3><div>The AUH program demonstrates a limited impact, particularly on health and nutrition outcome indicators. Efforts should be made to improve the program by focusing on cash transfer conditionality and amount, as well as strengthening healthcare infrastructure.</div></div><div><h3>Funding</h3><div>None.</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101011"},"PeriodicalIF":7.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Directly observed treatment for tuberculosis care and social support: essential lifeline or outdated burden?","authors":"Beatriz Barreto-Duarte ,&nbsp;Klauss Villalva-Serra ,&nbsp;Julio Croda ,&nbsp;Ricardo A. Arcêncio ,&nbsp;Ethel L.N. Maciel ,&nbsp;Bruno B. Andrade","doi":"10.1016/j.lana.2025.101015","DOIUrl":"10.1016/j.lana.2025.101015","url":null,"abstract":"","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101015"},"PeriodicalIF":7.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of cardiovascular risk: validation of a non-laboratory and a laboratory-based score in a Brazilian community-based cohort of the PURE study","authors":"Gustavo Bernardes de Figueiredo Oliveira ,&nbsp;Rafael Amorim Belo Nunes ,&nbsp;Lucas Bassolli de Oliveira Alves ,&nbsp;Precil Diego Miranda de Menezes Neves ,&nbsp;Victor Augusto Hamamoto Sato ,&nbsp;Ana Heloisa Kamada Triboni ,&nbsp;Haliton Alves de Oliveira Júnior ,&nbsp;Priscila Raupp da Rosa ,&nbsp;Maria Luz Díaz ,&nbsp;Jose Patricio Lopez-Jaramillo ,&nbsp;Fernando Lanas ,&nbsp;Philip Joseph ,&nbsp;Álvaro Avezum","doi":"10.1016/j.lana.2025.101009","DOIUrl":"10.1016/j.lana.2025.101009","url":null,"abstract":"<div><h3>Background</h3><div>Risk scores are essential tools for implementing cardiovascular disease (CVD) prevention. Validating risk scores considering regional diversities and disparities is critical for reducing the burden of CVD on global morbidity and mortality. We aimed to validate two cardiovascular risk scores (laboratory and non-laboratory-based) to predict major adverse cardiovascular events in the Brazilian cohort of the PURE study.</div></div><div><h3>Methods</h3><div>We validated two risk scores derived from the INTERHEART study, the non-laboratory INTERHEART risk score (NL-IHRS) and the laboratory fasting cholesterol INTERHEART risk score (FC-IHRS) using data from 4623 (urban areas) and 1415 (rural areas) participants without CVD in the Brazilian cohort of the PURE study enrolled in 2004 and 2005 and followed up to September 2021. The endpoint was major cardiovascular events (MACE), defined as the composite of myocardial infarction, stroke, heart failure, or death from cardiovascular causes. We evaluated the model performance of IHRS through c-statistic and calibration methods.</div></div><div><h3>Findings</h3><div>After a mean follow-up of 8.8 years (range, 0.28–15.1 years), there were 312 cardiovascular events, corresponding to an incidence rate of 0.58% per year (0.56% per year in urban versus 0.64% per year in rural areas). For the NL-IHRS, the c-statistic was 0.69 (95% confidence interval, CI, 0.66–0.72) in the overall cohort, 0.68 (95% CI, 0.64–0.72) in the urban cohort, and 0.72 (95% CI, 0.66–0.78) in the rural cohort. C-statistic values for the recalibrated FC-IHRS were 0.71 (95% CI, 0.67–0.74), 0.71 (95% CI, 0.67–0.75), and 0.70 (95% CI, 0.64–0.76) in the overall, urban, and rural cohorts, respectively.</div></div><div><h3>Interpretation</h3><div>In this Brazilian community-based prospective cohort, both NL-IHRS and FC-IHRS-based models performed with reasonable discriminative accuracy on the risk estimation of long-term risk of major CVD. A non-laboratory-based CVD risk score may be instrumental in Brazilian communities with limited access to medical resources.</div></div><div><h3>Funding</h3><div><span>Population Health Research Institute</span>, <span>Novartis Biociências S.A</span>.</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101009"},"PeriodicalIF":7.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hospital admissions for acute respiratory tract infections among infants from Nunavut and the burden of respiratory syncytial virus: a 10-year retrospective cohort study","authors":"Mai-Lei Woo Kinshella ,&nbsp;Jean Allen ,&nbsp;Jasmine Pawa ,&nbsp;Jesse Papenburg ,&nbsp;Radha Jetty ,&nbsp;Rachel Dwilow ,&nbsp;Joanne Embree ,&nbsp;Joan Robinson ,&nbsp;Laura Arbour ,&nbsp;Manish Sadarangani ,&nbsp;Ye Shen ,&nbsp;Jeffrey N. Bone ,&nbsp;Celia Walker ,&nbsp;Iryna Kayda ,&nbsp;Holden Sheffield ,&nbsp;Darcy Scott ,&nbsp;Amber Miners ,&nbsp;David M. Goldfarb","doi":"10.1016/j.lana.2025.101021","DOIUrl":"10.1016/j.lana.2025.101021","url":null,"abstract":"<div><h3>Background</h3><div>Nunavut is a northern Canadian territory where a high proportion of infants are admitted to hospital with acute respiratory tract infection (ARI). Previous studies have been limited in regional and/or short duration of coverage. This study aimed to estimate the incidence rate, microbiology and outcomes of ARI hospitalizations in Nunavut infants.</div></div><div><h3>Methods</h3><div>We conducted a retrospective cohort study of infants aged &lt;1 year from Nunavut hospitalized for ARI at two regional and four tertiary pediatric hospitals in Canada, January 1, 2010, to June 30, 2020. One regional hospital was located in Nunavut; others were located across Canada. Descriptive statistics and multivariable logistic regression were performed.</div></div><div><h3>Findings</h3><div>We identified 1189 ARI admissions, with an incidence rate of 133.9 per 1000 infants per year (95% confidence interval (CI): 126.8, 141.3). Of these admissions, 56.0% (n = 666) were to regional hospitals alone, 72.3% (n = 860) involved hospitalization outside of Nunavut, 15.6% (n = 185) were admitted into intensive care, and 9.2% (n = 109) underwent mechanical ventilation. Among 730 admissions with a pathogen identified, 45.8% had respiratory syncytial virus (RSV; n = 334), for a yearly incidence rate of 37.8 RSV-associated hospitalizations per 1000 infants (95% CI: 33.9, 42.1). Among RSV-associated hospitalizations, 41.1% (n = 138) were infants 0–2 months of age and 32.1% (n = 108) were &gt;6 months. Compared with non-RSV admissions, infants with RSV had higher odds of admission into intensive care, oxygen therapy, CPAP/BiPAP respiratory support and length of hospital stay over a week.</div></div><div><h3>Interpretation</h3><div>Understanding the high burden of ARI among Nunavut infants can inform health policy and serve as a baseline for assessing the impact of any new interventions targeting infant ARIs.</div></div><div><h3>Funding</h3><div><span>Public Health Agency of Canada</span> and Canadian Institutes of Health Research via the <span>Canadian Immunization Research Network</span> (CNF 151944).</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101021"},"PeriodicalIF":7.0,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perinatal health outcomes of offspring of internal migrant women according to human development index: a registry-based cohort study of over 10 million live births from Brazil","authors":"Thiago Cerqueira-Silva ,&nbsp;Enny S. Paixao ,&nbsp;Ila R. Falcao ,&nbsp;Joanna M.N. Guimarães ,&nbsp;Laura C. Rodrigues ,&nbsp;Alisson Baribieri ,&nbsp;Ibrahim Ababukar ,&nbsp;Mauricio L. Barreto ,&nbsp;Julia M. Pescarini","doi":"10.1016/j.lana.2025.101020","DOIUrl":"10.1016/j.lana.2025.101020","url":null,"abstract":"<div><h3>Background</h3><div>Migration, driven by factors like poverty, violence, and natural disasters, is a key social determinant of health. While international migrants often have worse perinatal outcomes, research on perinatal health differences between internal migrants and non-migrants remains limited. We aimed to determine whether the offspring of women who migrate within Brazil experience poorer perinatal outcomes than those of non-migrants, according to the Human Development Index (HDI) of their municipalities of origin and destination.</div></div><div><h3>Methods</h3><div>We used the CIDACS Birth Cohort, consisting of women applying for social programmes in the Unified Registry for Social Programmes <em>Cadastro Único</em> linked with live births and mortality registries. We included live births conceived from March 2010 to February 2018. Internal migrants were women who changed their state of residence from registration in CadUnico to the birth of the child. We derived risk ratios (RR) of migration's effect according to HDI of residence before and after migration using logistic regression.</div></div><div><h3>Findings</h3><div>We included 10,184,021 births in the study, with 5.7% of these births from women who were internal migrants. The offspring of women who migrated to municipalities with equal/higher HDI (80% of migrations), exhibited a decreased risk of preterm births (RR: 0.94, 95% CI: 0.93–0.95), low birth weight (RR: 0.94, 95% CI: 0.92–0.95) and small for gestational age (RR: 0.92, 95% CI: 0.91–0.93), but higher risk of congenital abnormalities (RR: 1.14, 95% CI: 1.10–1.18). The offspring of women who migrated to municipalities with lower HDI had delayed access to healthcare and worse outcomes except for a lower risk of low birth weight (RR: 0.94, 95% CI: 0.92–0.96).</div></div><div><h3>Interpretation</h3><div>Offspring of those migrating to municipalities with equal/higher HDI tend to have better perinatal outcomes, whereas migrants to lower HDIs have a similar pattern to non-migrant women.</div></div><div><h3>Funding</h3><div><span>NIHR</span>, <span>Wellcome Trust</span>, Royal Society.</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101020"},"PeriodicalIF":7.0,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mental health impacts of air disasters: a call for a coordinated response to Brazil’s christmas tragedy","authors":"Felipe Ornell ,&nbsp;Juliana Nichterwitz Scherer ,&nbsp;Daniel Prates-Baldez ,&nbsp;Simone Hauck ,&nbsp;Flavio Kapczinski","doi":"10.1016/j.lana.2025.101016","DOIUrl":"10.1016/j.lana.2025.101016","url":null,"abstract":"","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101016"},"PeriodicalIF":7.0,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143388315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time series forecasting of Valley fever infection in Maricopa County, AZ using LSTM","authors":"Xueting Jin ,&nbsp;Fangwu Wei ,&nbsp;Srinivasa Srivatsav Kandala ,&nbsp;Tejas Umesh ,&nbsp;Kayleigh Steele ,&nbsp;John N. Galgiani ,&nbsp;Manfred D. Laubichler","doi":"10.1016/j.lana.2025.101010","DOIUrl":"10.1016/j.lana.2025.101010","url":null,"abstract":"<div><h3>Background</h3><div>Coccidioidomycosis (CM), also known as Valley fever, is a respiratory infection. Recently, the number of confirmed cases of CM has been increasing. Precisely defining the influential factors and forecasting future infection can assist in public health messaging and treatment decisions.</div></div><div><h3>Methods</h3><div>We utilized Long Short-Term Memory (LSTM) networks to forecast CM cases, based on the daily pneumonia cases in Maricopa County, Arizona from 2020 to 2022. Besides weather and climate variables, we examined the impact of people's lifestyle change during COVID-19. Factors, including temperature, precipitation, wind speed, PM₁₀ and PM_2.5 concentration, drought, and stringency index, were included in LSTM networks, considering their association with CM prevalence, time-lag effect, and correlation with other factors.</div></div><div><h3>Findings</h3><div>LSTM can predict CM prevalence with accurate trend and low mean squared error (MSE). We also found a tradeoff between the length of the forecasting period and the performance of the forecasting model. The models with longer forecasting periods have less accurate trends over time and higher MSEs. Two models with different lengths of forecasting periods, 10 days and 30 days, are identified with good prediction.</div></div><div><h3>Interpretation</h3><div>LSTM algorithms, combined with traditional statistical methods, could help with the forecasting of CM cases. By predicting the CM prevalence, our results can inform researchers, epidemiologists, clinicians, and the public in order to assist public health.</div></div><div><h3>Funding</h3><div>“Getting to the Source of Arizona's Valley Fever Problem: A Tri-University Collaboration to Map and Characterize the Pathogen Where It Grows” funded by the <span>Arizona Board of Regents</span>.</div></div>","PeriodicalId":29783,"journal":{"name":"Lancet Regional Health-Americas","volume":"43 ","pages":"Article 101010"},"PeriodicalIF":7.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143131553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}