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Nevin Manimala Statistics

Impact of Primary Health Care Data Quality on Infectious Disease Surveillance in Brazil: Case Study

JMIR Public Health Surveill. 2025 Feb 21;11:e67050. doi: 10.2196/67050.

ABSTRACT

BACKGROUND: The increase in emerging and re-emerging infectious disease outbreaks underscores the need for robust early warning systems (EWSs) to guide mitigation and response measures. Administrative health care databases provide valuable epidemiological insights without imposing additional burdens on health services. However, these datasets are primarily collected for operational use, making data quality assessment essential to ensure an accurate interpretation of epidemiological analysis. This study focuses on the development and implementation of a data quality index (DQI) for surveillance integrated into an EWS for influenza-like illness (ILI) outbreaks using Brazil’s a nationwide Primary Health Care (PHC) dataset.

OBJECTIVE: We aimed to evaluate the impact of data completeness and timeliness on the performance of an EWS for ILI outbreaks and establish optimal thresholds for a suitable DQI, thereby improving the accuracy of outbreak detection and supporting public health surveillance.

METHODS: A composite DQI was established to measure the completeness and timeliness of PHC data from the Brazilian National Information System on Primary Health Care. Completeness was defined as the proportion of weeks within an 8-week rolling window with any register of encounters. Timeliness was calculated as the interval between the date of encounter and its corresponding registry in the information system. The backfilled PHC dataset served as the gold standard to evaluate the impact of varying data quality levels from the weekly updated real-time PHC dataset on the EWS for ILI outbreaks across 5570 Brazilian municipalities from October 10, 2023, to March 10, 2024.

RESULTS: During the study period, the backfilled dataset recorded 198,335,762 ILI-related encounters, averaging 8,623,294 encounters per week. The EWS detected a median of 4 (IQR 2-5) ILI outbreak warnings per municipality using the backfilled dataset. Using the real-time dataset, 12,538 (65%) warnings were concordant with the backfilled dataset. Our analysis revealed that 100% completeness yielded 76.7% concordant warnings, while 80% timeliness resulted in at least 50% concordant warnings. These thresholds were considered optimal for a suitable DQI. Restricting the analysis to municipalities with a suitable DQI increased concordant warnings to 80.4%. A median of 71% (IQR 54%-71.9%) of municipalities met the suitable DQI threshold weekly. Municipalities with ≥60% of weeks achieving a suitable DQI demonstrated the highest concordance between backfilled and real-time datasets, with those achieving ≥80% of weeks showing 82.3% concordance.

CONCLUSIONS: Our findings highlight the critical role of data quality in improving the EWS’ performance based on PHC data for detecting ILI outbreaks. The proposed framework for real-time DQI monitoring is a practical approach and can be adapted to other surveillance systems, providing insights for similar implementations. We demonstrate that optimal completeness and timeliness of data significantly impact the EWS’ ability to detect ILI outbreaks. Continuous monitoring and improvement of data quality should remain a priority to strengthen the reliability and effectiveness of surveillance systems.

PMID:39983017 | DOI:10.2196/67050

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Nevin Manimala Statistics

Predicting Fitness-Related Traits Using Gene Expression and Machine Learning

Genome Biol Evol. 2025 Feb 3;17(2):evae275. doi: 10.1093/gbe/evae275.

ABSTRACT

Evolution by natural selection occurs at its most basic through the change in frequencies of alleles; connecting those genomic targets to phenotypic selection is an important goal for evolutionary biology in the genomics era. The relative abundance of gene products expressed in a tissue can be considered a phenotype intermediate to the genes and genomic regulatory elements themselves and more traditionally measured macroscopic phenotypic traits such as flowering time, size, or growth. The high dimensionality, low sample size nature of transcriptomic sequence data is a double-edged sword, however, as it provides abundant information but makes traditional statistics difficult. Machine learning (ML) has many features which handle high-dimensional data well and is thus useful in genetic sequence applications. Here, we examined the association of fitness components with gene expression data in Ipomoea hederacea (Ivyleaf morning glory) grown under field conditions. We combine the results of two different ML approaches and find evidence that expression of photosynthesis-related genes is likely under selection. We also find that genes related to stress and light responses were overall important in predicting fitness. With this study, we demonstrate the utility of ML models for smaller samples and their potential application for understanding natural selection.

PMID:39983007 | DOI:10.1093/gbe/evae275

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Nevin Manimala Statistics

A 1600-year record of extreme rainfall in northern Arabia

Sci Adv. 2025 Feb 21;11(8):eadq3173. doi: 10.1126/sciadv.adq3173. Epub 2025 Feb 21.

ABSTRACT

Intense rain can trigger flashfloods in Arabia. Torrential rains in 2024 sowed widespread chaos in the region. Sediment-loaded plumes discharged by flashfloods deposit onto the seabed. Burrowing animals disrupt these flood layers, erasing the paleorainfall record. Fortuitously, we discovered an anoxic deep-sea brine pool sited close enough to shore to chronicle floods, yet be otherwise undisturbed by animals. Cores retrieved from the pool delivered a 1600-year rainfall record. We merge these core-layer histories with modern rainfall statistics, satellite observations, and simulations to deliver a high-resolution quantitative Late Holocene hydroclimate record for Arabia. We find that the modern era is 2.5 times drier than the last 1.6 thousand years. The Little Ice Age stands out as particularly wet. That period experienced a fivefold increase in rainfall intensity compared to today. Though hyperarid now, the flood layers demonstrate that climate shifts can generate weather conditions unwitnessed in the modern era. Such long-range insight is crucial for framing uncertainties surrounding future hydroclimate forecasts.

PMID:39982992 | DOI:10.1126/sciadv.adq3173

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Nevin Manimala Statistics

Perceptions and predictors of COVID-19 vaccine hesitancy among healthcare providers across five countries in sub-Saharan Africa

PLOS Glob Public Health. 2025 Feb 21;5(2):e0003956. doi: 10.1371/journal.pgph.0003956. eCollection 2025.

ABSTRACT

The African continent has some of the world’s lowest COVID-19 vaccination rates. While the limited availability of vaccines is a contributing factor, COVID-19 vaccine hesitancy among healthcare providers (HCP) is another factor that could adversely affect efforts to control infections on the continent. We sought to understand the extent of COVID-19 vaccine hesitancy among HCP, and its contributing factors in Africa. We evaluated COVID-19 vaccine hesitancy among 1,499 HCP enrolled in a cross-sectional study conducted as a telephone survey in Burkina Faso, Ethiopia, Nigeria, Tanzania, and Ghana between July to December of 2021. We defined COVID-19 vaccine hesitancy among HCP as self-reported responses of definitely not, maybe, unsure, or undecided on whether to get the COVID-19 vaccine, compared to definitely getting the vaccine. We used log-binomial or modified Poisson regression models to evaluate factors influencing vaccine hesitancy among HCP. Approximately 65.6% of the HCP interviewed were nurses and the mean age (±SD) of participants was 35.8 (±9.7) years. At least 67% of the HCP reported being vaccinated. COVID-19 vaccine hesitancy affected 45.7% of the HCP in Burkina Faso, 25.7% in Tanzania, 9.8% in Ethiopia, 9% in Ghana and 8.1% in Nigeria. Among unvaccinated HCP reasons for low vaccine uptake included concern about vaccine effectiveness, side effects, and fear of receiving experimental and unsafe vaccines. HCP reporting that COVID-19 vaccines are very effective (RR: 0.21, 95% CI: 0.08, 0.55), and older HCP (45 or older vs.20-29 years, RR: 0.65, 95% CI: 0.44, 0.95) were less likely to be vaccine-hesitant. Nurses were more likely to be vaccine-hesitant (RR 1.38, 95% CI: 1.01, 1.89) than doctors. Information asymmetry among HCP, beliefs about vaccine effectiveness, and the endorsement of vaccines by public health institutions may be important. Efforts to address hesitancy should consider information and knowledge gaps among different cadres of HCP alongside efforts to increase vaccine supply.

PMID:39982973 | DOI:10.1371/journal.pgph.0003956

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Nevin Manimala Statistics

Cancer in English prisons: a mixed-methods study of diagnosis, treatment, care costs and patient and staff experiences

Health Soc Care Deliv Res. 2025 Feb;13(3):1-51. doi: 10.3310/HYRT9622.

ABSTRACT

BACKGROUND: The increasing size of the ageing English prison population means that non-communicable diseases such as cancer are being more commonly diagnosed in this setting. Little research has so far considered the incidence of cancer in the English prison population, the treatment patients receive when they are diagnosed in a prison setting, their care costs and outcomes or their experiences of care compared with those of people diagnosed in the general population. This is the first mixed-methods study that has been designed to investigate these issues in order to inform recommendations for cancer practice, policy and research in English prisons.

METHODS: We compared cancer diagnoses made in prison between 1998 and 2017 with those made in the general population using a cohort comparison. We then used a cohort comparison approach to patients’ treatment, survival, care experiences and costs of care between 2012 and 2017. We also conducted qualitative interviews with 24 patients diagnosed or treated in prison, and 6 custodial staff, 16 prison health professionals and 9 cancer professionals. Findings were presented to senior prison and cancer stakeholders at a Policy Lab event to agree priority recommendations.

RESULTS: By 2017 cancer incidence in prison had increased from lower levels than in the general population to similar levels. Men in prison developed similar cancers to men outside, while women in prison were more likely than women outside to be diagnosed with preinvasive cervical cancer. In the comparative cohort study patients diagnosed in prison were less likely to undergo curative treatment, particularly surgery, and had a small but significantly increased risk of death. They also had fewer but slightly longer emergency hospital admissions, lower outpatient costs and fewer planned inpatient stays. While secondary care costs were lower for patients in prison, when security escorts costs were added, emergency care and total costs were higher. Control and choice, communication, and care and custody emerged as key issues from the qualitative interviews. People in prison followed a similar diagnostic pathway to those in the general population but experienced barriers arising from lower health literacy, a complex process for booking general practitioner appointments, communication issues between prison staff, surgical, radiotherapy and oncology clinicians and a lack of involvement of their family and friends in their care. These issues were reflected in patient experience survey results routinely collected as part of the annual National Cancer Patient Experience Survey. The four priorities developed and agreed at the Policy Lab event were giving clinical teams a better understanding of the prison system, co-ordinating and promoting national cancer screening programmes, developing ‘health champions’ in prison and raising health literacy and awareness of cancer symptoms among people in prison.

LIMITATIONS: We could not identify patients who had been diagnosed with cancer before entering prison.

CONCLUSION: Healthcare practices and policies both within prisons and between prisons and NHS hospitals need to be improved in a range of ways if the cancer care received by people in prison is to match that received by the general population.

FUTURE WORK: Evaluating new policy priorities.

FUNDING: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 16/52/53) and is published in full in Health and Social Care Delivery Research; Vol. 13, No. 3. See the NIHR Funding and Awards website for further award information.

PMID:39982760 | DOI:10.3310/HYRT9622

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Nevin Manimala Statistics

MLR Data-Driven for the Prediction of Infinite Dilution Activity Coefficient of Water in Ionic Liquids (ILs) Using QSPR-Based COSMO Descriptors

J Chem Inf Model. 2025 Feb 21. doi: 10.1021/acs.jcim.4c02095. Online ahead of print.

ABSTRACT

To predict the partial molar excess enthalpy, entropy at infinite dilution, and phase equilibria, the availability of an infinite dilution activity coefficient is vital. The “quantitative structure-activity/property relationship” (QSAR/QSPR) approach has been used for the prediction of infinite dilution activity coefficient of water in ionic liquids using an extensive data set. The data set comprised 380 data points including 68 unique ILs at a wide range of temperatures, which is more extensive than previously published data sets. Moreover, new predictive QSAR/QSPR models including novel molecular descriptors, called “COSMO-RS descriptors”, have been developed. Using two different techniques of external validation, the data set was divided to the training set for the development of models and to the validation set for external validation. Unlike former available models, internal validation using leave one/multi out-cross validations (LOO-CV/LMO-CV) and Y-scrambling methods were performed on the models using statistical parameters for further assessment. According to the obtained results of statistical parameters (R2 = 0.99 and Q2LOO-CV = 0.99), the predictive capability of the developed QSPR model was excellent for training set. Regarding the external validation, other statistical parameters such as AAD = 0.283 and AARD % = 30 were also satisfactory for the validation set. While the values of γH2O increase or decrease with increasing temperature, the QSAR/QSPR models based on the van’t Hoff equation takes into account the negative and positive effects of temperature on the γH2O in ILs well, depending on the nature of ILs. It was also shown that γH2O in some new ILs which had not been experimentally studied before can be predicted using the QSPR model.

PMID:39982758 | DOI:10.1021/acs.jcim.4c02095

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Nevin Manimala Statistics

Investigation and Analysis of Staphylococcus aureus Contamination in Food in Yantai City, China: Based on a 14-Year Continuous Monitoring

Foodborne Pathog Dis. 2025 Feb 21. doi: 10.1089/fpd.2024.0175. Online ahead of print.

ABSTRACT

Staphylococcus aureus is a foodborne zoonotic pathogen that threatens food safety and public health. However, few people have conducted long-term and systematic studies on S. aureus contamination in food in Yantai City. To investigate the contamination situation of S. aureus in food and improve the ability of early warning and control of foodborne diseases, a total of 2384 samples from 17 categories were collected from 13 monitoring points in Yantai City, from 2010 to 2023. Forty-four samples were positively detected for S. aureus, with a detection rate of 1.85% (44/2384). The detection rate of S. aureus was highest in Zhifu District (4.12%), followed by Penglai District (2.45%), Zhaoyuan District (2.37%), Kaifa District (2.19%), and Longkou District (1.98%). Positive detection rates were higher in frozen rice and flour products at 8.82% (6/68), quick-frozen dishes at 5.56% (1/18), aquatic products at 4.05% (3/74), and meat and meat products at 3.55% (27/760). Positive detection rates in samples from the first, second, third, and fourth quarters were 0% (0/44), 2.21% (20/906), 2.13% (22/1033), and 0.50% (2/401), respectively. Positive detection rates in bulk and prepackaged samples were 2.33% (36/1546) and 0.95% (8/838), respectively, with statistically significant differences (χ2 = 5.66, p < 0.05). Positive detection rates were significantly different for samples collected from different sampling stages, of which at production and processing stages was 7.78% (20/257), catering stages 1.38% (10/727), and distribution stages 1% (14/1400) (χ2 = 56.41, p < 0.05). Frozen rice and flour products, quick-frozen dishes, aquatic products, and meat and meat products are the main food products contaminated with S. aureus, and the resulting secondary contamination is a hidden danger for the occurrence of foodborne diseases, which should be given sufficient attention.

PMID:39982751 | DOI:10.1089/fpd.2024.0175

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Nevin Manimala Statistics

Entanglement transition in random rod packings

Proc Natl Acad Sci U S A. 2025 Feb 25;122(8):e2401868122. doi: 10.1073/pnas.2401868122. Epub 2025 Feb 21.

ABSTRACT

Random packings of stiff rods are self-supporting mechanical structures stabilized by long-range interactions induced by contacts. To understand the geometrical and topological complexity of the packings, we first deploy X-ray computerized tomography to unveil the structure of the packing. This allows us to directly visualize the spatial variations in density, orientational order, and the entanglement, a mesoscopic field that we define in terms of a local average crossing number, a measure of the topological complexity of the packing. We find that increasing the aspect ratio of the constituent rods in a packing leads to a proliferation of regions of strong entanglement that eventually percolate through the system and correlated with a sharp transition in the mechanical stability of the packing. To corroborate our experimental findings, we use numerical simulations of contacting elastic rods and characterize their stability to static and dynamic loadings. Our experiments and computations lead us to an entanglement phase diagram which we also populate using published experimental data from pneumatically tangled filaments, worm blobs, and bird nests along with additional numerical simulations using these datasets. Together, these show the regimes associated with mechanically stable entanglement as a function of the statistics of the packings and loading, with lessons for a range of systems from reconfigurable architectures and textiles to active morphable filamentous assemblies.

PMID:39982741 | DOI:10.1073/pnas.2401868122

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Nevin Manimala Statistics

Prevalence, Trajectory, and Factors Associated With Patient-Reported Nonmotor Outcomes After Stroke: A Systematic Review and Meta-Analysis

JAMA Netw Open. 2025 Feb 3;8(2):e2457447. doi: 10.1001/jamanetworkopen.2024.57447.

ABSTRACT

IMPORTANCE: The evidence on nonmotor outcomes after acute ischemic stroke and intracerebral hemorrhage (ICH) is limited and domain-specific. The prevalence, natural history, and factors associated with nonmotor outcomes across multiple domains are unclear.

OBJECTIVE: To synthesize the published data and to identify the prevalence, natural history, and factors associated with multidomain nonmotor outcome burden in patients with stroke.

DATA SOURCES: A search of PubMed, MEDLINE, EMBASE, and PsycINFO databases between January 1999 to June 2023 was supplemented by search of bibliographies of the key articles.

STUDY SELECTION: The analysis included prospective cohort studies that reported nonmotor outcomes across 10 domains: anxiety, depression, fatigue, sleep disturbance, social participation, pain, bladder dysfunction, bowel dysfunction (constipation and fecal incontinence), and sexual dysfunction assessed by patient-reported scales.

DATA EXTRACTION AND SYNTHESIS: Two reviewers independently assessed studies, extracting baseline data, nonmotor prevalence, and follow-up information. Pooled prevalence of nonmotor outcomes was estimated using random-effects models. Meta-regression models were used to analyze natural history and factors associated with nonmotor outcomes. Subgroup analysis was used to assess prevalence by symptom description within each nonmotor domain. Publication bias and study quality were assessed using funnel plots and the Newcastle-Ottawa scale.

RESULTS: A total of 279 prospective cohort studies met the inclusion criteria (117 440 participants with stroke; median [IQR] age, 65 [59-70] years; 209 of 279 studies with more male than female participants) with a nonmotor outcome follow-up period ranging from 30 days to 10 years after stroke. The most prevalent adverse nonmotor outcomes by pooled prevalence were sleep disturbance (59.9%; 95% CI, 53.9%-63.9%), sexual dysfunction (59.8%; 95% CI, 50.0%-69.5%), constipation (58.2%; 95% CI, 53.9%-62.6%), reduced social participation (56.5%; 95% CI, 52.1%-60.8%), bladder dysfunction (45.9%; 95% CI, 38.0%-53.8%), and fatigue (45.2%; 95% CI, 40.7%-49.5%). Meta-regression analysis showed no significant improvement over time for most nonmotor outcomes, except pain (coefficient = -11.0%; P = .05) and sexual dysfunction (coefficient = -24.1%; P < .001). The heterogeneity ranged between 52% and 98% across all studies. The common factors associated with adverse nonmotor outcomes were female sex, studies with mixed stroke cohort (ischemic stroke or ICH), and older age.

CONCLUSIONS AND RELEVANCE: Patient-reported nonmotor outcomes were common after stroke. Sexual dysfunction, sleep disturbance, constipation, reduced social participation, bladder dysfunction, and fatigue were most prevalent. These adverse outcomes often persisted over time, especially in women, older adults, and those in studies with mixed stroke cohorts.

PMID:39982730 | DOI:10.1001/jamanetworkopen.2024.57447

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Algorithm-Based Palliative Care in Patients With Cancer: A Cluster Randomized Clinical Trial

JAMA Netw Open. 2025 Feb 3;8(2):e2458576. doi: 10.1001/jamanetworkopen.2024.58576.

ABSTRACT

IMPORTANCE: Among patients with advanced solid malignant tumors, early specialty palliative care (PC) is guideline recommended, but strategies to increase PC access and effectiveness in community oncology are lacking.

OBJECTIVE: To test whether algorithm-based defaults with opting out and accountable justification embedded in the electronic health record (EHR) increase completed PC visits.

DESIGN, SETTING, AND PARTICIPANTS: This 2-arm cluster randomized clinical trial was conducted from November 1, 2022, to December 31, 2023. Eligible patients from 15 urban or rural clinics within a large community oncology network in Tennessee had advanced lung or noncolorectal gastrointestinal cancer and were identified by an automated EHR algorithm adapted from national guidelines. Data were analyzed between November 1, 2023, and March 4, 2024.

INTERVENTION: At sites randomized to control, clinicians received weekly reports detailing PC referral rates compared with peer clinicians (peer comparison) and referred patients to PC at their discretion. At sites randomized to intervention, clinicians also received default PC orders using the EHR. Clinicians who opted out of PC consultation were asked to provide justification (accountable justification). If clinicians did not opt out, a study coordinator contacted patients to introduce and schedule PC visits using a standardized, predefined script.

MAIN OUTCOMES AND MEASURES: The primary outcome was a completed PC consultation within 12 weeks of enrollment. Exploratory outcomes included quality of life, feeling heard and understood, and intensive end-of-life care. Outcomes were analyzed using clustered generalized linear and logistic regression models.

RESULTS: The trial enrolled 562 patients (mean [SD] age, 68.5 [10.1] years; 288 male [51.2%]), of whom 433 (77.0%) had lung cancer. There were 130 of 296 patients (43.9%) randomized to the intervention group and 22 of 266 (8.3%) randomized to the control group who completed PC visits (adjusted odds ratio, 8.9 [95% CI, 5.5-14.6]; P < .001). Among 179 patients who died at the 24-week follow-up, 6 of 92 (6.5%) in the intervention group compared with 14 of 87 (16.1%) in the control group received systemic therapy within 14 days of death (adjusted odds ratio, 0.3 [95% CI, 0.1-0.7]; P = .05). There were no differences in quality of life, feeling heard and understood, or late hospice referral.

CONCLUSIONS AND RELEVANCE: In this randomized clinical trial of algorithm-based EHR defaults, the intervention increased PC consultations and decreased end-of-life systemic therapy. The intervention provides a scalable implementation strategy to increase specialty PC referrals in the community oncology setting.

TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT05590962.

PMID:39982729 | DOI:10.1001/jamanetworkopen.2024.58576