Tropical Medicine and Infectious Disease最新文献

Objective: The aim was to analyze the temporal evolution and spatial distribution of classic and hemorrhagic dengue in the Mexican state of San Luis Potosí at the basic geostatistical area (BGA) level and to develop multivariate models to estimate the population's degree of vulnerability.

Methodology: Classic and hemorrhagic dengue cases for 2015-2020 were obtained from the Mexican Ministry of Health, georeferenced at the pixel level, and subsequently grouped by BGA. Environmental, proximity, and social variables were obtained from official sites: IMTA, SMN, USGS, and INEGI. Multivariate logistic regression models were developed using PASW Statistics v. 18 software to estimate the degree of vulnerability, and the receiver operating characteristic curve was used to validate them.

Results: A total of 125, 128, 109, 624, 1580, and 1817 dengue cases were identified for 2015, 2016, 2017, 2018, 2019, and 2020, respectively. The major factors contributing to the vulnerability of classic dengue fever included population, temperature, and distance to agricultural areas. For hemorrhagic dengue, the contributing factors were temperature, population, and mean annual rainfall. Vulnerability prediction was determined by taking the area under the curve values, which were 0.957 for classic dengue fever and 0.930 for hemorrhagic dengue, both indicating a "very good ability" to predict.

Conclusions: These results can be used to design and implement targeted strategies, particularly for modifiable factors, such as prevention measures directed towards populated areas and the improvement of sewage systems, in addition to non-modifiable factors, such as temperature and rainfall. This method can be replicated as an additional tool to address this public health issue.

Tuberculosis preventive treatment (TPT) is a mainstay for reducing the tuberculosis (TB) burden among people living with human immunodeficiency virus (PLHIV). Context-specific challenges hinder TPT uptake and completion among PLHIV. During 2022-2024, a mixed-methods design was used to evaluate the TPT cascade and explore its facilitators and barriers among PLHIV availing care from 12 PEPFAR-supported health facilities in Uganda. The quantitative component included analysis of routine programmatic data, and the qualitative component included focus group discussions and in-depth interviews with healthcare workers and PLHIV. A total of 1349 PLHIV were enrolled in the evaluation. Among PLHIV newly initiated on ART (≤3 months), 74% started TPT, and 98% of them completed it. In PLHIV already on ART, 87% had initiated TPT (76% before and 11% during this evaluation), with a treatment completion rate of 98%. The facilitators for TPT implementation included access to shorter TPT regimens, integration of services, and adherence counseling. Barriers included knowledge gaps, pill burden, TPT drug stock-outs, and documentation inconsistencies. The TPT completion rate was higher than the national target (90%), but the TPT initiation remains low. Improved access to shorter regimens, adherence counseling, better documentation, and service integration can sustain the completion rate and improve the initiation rate in Uganda and possibly elsewhere.

Background: Most of the currently approved TB diagnostics are sputum-based. However, due to unusual clinical presentations of TB among HIV patients, they may not have TB symptoms and be able to produce sputum. Hence, these diagnostics may not be able to detect as many TB cases as possible among these patients. Therefore, this study assessed the performance of C-reactive protein (CRP) and interferon-gamma-inducible protein 10 (IP-10) as a screening tool for TB.

Methods: This prospective study was conducted by consecutively recruiting patients with TB symptoms, collecting their sputum and blood samples, using sputum culture as the reference standard, and determining the best cut-off point of serum levels of CRP and IP-10 (separately and in combination) for TB diagnosis.

Findings: CRP and IP-10 were measured in 408 patients with TB symptoms, of which 21% had culture-confirmed TB. CRP's sensitivity and specificity were (91.4% and 33.2%), (95.3% and 42.6%) and (84.8% and 22.1%) for the whole study population, HIV-negative and HIV-positive patients, respectively. The sensitivity and specificity of IP-10 were (87.3% and 40.9%), (87.5% and 50.3%) and (79.4% and 47.2%) for the patients' categories, respectively. Combination of CRP and IP-10 slightly improved the performance of the biomarkers among HIV-negative patients, with sensitivity of 97.5% and specificity of 43.3%.

Interpretation: Though CRP and IP-10 performed better in HIV-negative patients than among people living with HIV (PLHIV), the performance of the biomarkers is lower than what is recommended by the WHO (sensitivity ≥ 90% and specificity ≥ 70%) for a TB screening tool. Hence, there is a need for better non-sputum-based TB diagnostics.

Background. West Nile Virus (WNV) represents a significant public health concern in Europe, with Italy-particularly its northern regions-experiencing recurrent outbreaks. Climate variables and vector dynamics are known to significantly influence transmission patterns, highlighting the need for reliable predictive models to enable timely outbreak detection and response. Methods. We integrated epidemiological data on human WNV infections in Italy (2012-2024) with high-resolution climate variables (temperature, humidity, and precipitation). Using advanced feature engineering and a gradient boosting framework (XGBoost), we developed a predictive model optimized through time-series cross-validation. Results. The model achieved high predictive accuracy at the national level (R² = 0.994, MAPE = 5.16%) and maintained robust performance across the five most affected provinces, with R² values ranging from 0.896 to 0.996. SHAP analysis identified minimum temperature as the most influential climate predictor, while maximum temperature and rainfall demonstrated considerably weaker associations with case incidence. Conclusions. This machine learning approach provides a reliable framework for forecasting WNV outbreaks and supports evidence-based public health responses. The integration of climate and epidemiological data enhances surveillance capabilities and enables informed decision-making at regional and local levels.

Background: Cryptococcosis, a systemic mycosis, remains a neglected disease in Brazil due to the absence of systematic national surveillance. This study developed an interactive dashboard to analyze cryptococcosis-related deaths (2000-2022) and forecast trends through regional ARIMA modeling. Methodology: The Cross-Industry Standard Process for Data Mining framework was employed to extract mortality data from the Brazilian Mortality Information System, utilizing the microdatasus package in R Studio software, with R version 3.4.0. The records were then filtered using the International Classification of Diseases, Tenth Revision codes (B45 series) to identify primary and associated causes of death. After data extraction, a series of data preprocessing steps was implemented, including deduplication, variable recoding, and the management of missing values. The Shiny framework was employed to construct an interactive dashboard, incorporating Plotly and DT packages, with time-series visualizations, demographic variables, and multilingual support (Portuguese/English). Results: Among 12,308 deaths (2227 primary; 10,081 associated causes), most occurred in males aged 21-60 years. Data completeness was high for age/residence (100%) but lower for education (82%). The dashboard enables dynamic exploration of trends, demographic patterns, and open-data downloads. Regional ARIMA models revealed heterogeneous forecasts, with the Southeast projecting a decline (193 deaths in 2025; 95% CI: 146-240) and the South showing stability (141 deaths; 95% CI: 109-173). Conclusions: This tool bridges a critical gap in cryptococcosis surveillance, enabling dynamic mortality trend analysis, identification of high-risk demographics, and regional forecasting to guide public health resource allocation. While the absence of HIV serostatus data limits etiological analysis, the dashboard's open-source framework supports adaptation for other neglected diseases.

Brucellosis is a widespread zoonotic disease and a major contributor to febrile illness, often underdiagnosed. This study investigated the seroprevalence of brucellosis and the associated exposure factors within South African farming and animal health communities. A cross-sectional survey was conducted across 40,000 km² in the Free State and Northern Cape provinces from 2015 to 2016. Interviews and serum samples were collected from 847 volunteers on randomly selected farms and veterinary professionals listed in a regional register. Samples were tested using a commercial Brucella IgG ELISA. Risk factors were assessed using logistic regression, accounting for within-farm clustering. The seroprevalence was higher among veterinary professionals (11.6%; 16/138) than farm-based participants (7.0%; 50/711); p = 0.095. Multivariable analysis identified several exposure factors within the farm-based population: age over 40 years (aOR = 5.35; 95% CI: 1.68-17.02), White population group (aOR = 4.60; 95% CI: 1.64-12.91), contact with diseased animals (aOR = 2.01; 95% CI: 1.05-3.84), and working 4-8 h daily with ungulates (aOR = 2.90; 95% CI: 1.25-6.76). Among veterinary professionals, odds of exposure were higher with more than 5 years of work (OR = 1.82; 95% CI: 1.21-2.72) and extended ungulate contact (OR = 4.85; 95% CI: 1.27-18.52). Occupational exposure highlights the need for improved brucellosis prevention strategies.

Empirical antibiotic treatment is common in acute conjunctivitis despite most cases being non-infectious or viral infections. Operational research (OR) at an eye hospital in Ghana (January-December 2021) identified appropriate antibiotic prescription in 71% of cases. Research dissemination and the sensitisation of key stakeholders followed, including communication of findings and implications to hospital prescribers. We conducted this OR covering January-December 2024 to test the hypothesis that the appropriateness of antibiotic prescriptions will improve, and to investigate the types of antibiotics prescribed and their AWaRe classification. There were 220 acute conjunctivitis cases in 2024, comparable to 2021 (201 cases). Antibiotics were prescribed in 67% of cases in 2024 and 55% in 2021 (aOR 2.51, 95% CI: 1.51-4.19, p < 0.001). Antibiotic prescription appropriateness was higher in 2024 than in 2021: 87% and 71%, respectively (95% CI for change: 5.99-25.99%, p = 0.001). In 2021, only ACCESS and WATCH antibiotics were prescribed. However, 15% of prescriptions in 2024 were RESERVE antibiotics, and multiple antibiotic prescriptions increased from 10% to 22%. This research demonstrates that regular operational research and interventions have the potential to improve antibiotic prescribing in ophthalmic practice in Ghana. It is imperative that the recommendations made by the initial researchers are fully implemented to protect the efficacy of available antibiotics.

Background: In recent decades, malaria vector species distribution and insecticide resistance have taken new colonization steps across Africa. Understanding the malaria vector insecticide resistance status, blood meal source, and species composition is of paramount importance in designing evidence-based vector control strategies. This study assessed the blood meal sources, sporozoite (infectivity) rate, and knockdown resistance allele's frequency in female Anopheles arabiensis in chosen villages of Jabi Tehnan District, Northwest Ethiopia. Methods: The host-seeking and resting Anopheles gambiae s.l. were collected using human landing catches (HLCs), CDC light traps (CDC-LTs), pyrethrum spray catches (PSCs), and pit shelters (PSs) both indoors and outdoors. The analysis of both blood meal sources and circumsporozoite proteins was performed using enzyme-linked immunosorbent assay (ELISA). The detection of knockdown resistance gene mutations and species identification were conducted using a polymerase chain reaction (PCR). Results: A total of 5098 female Anopheles gambiae s.l. were collected. Of these, 1690 (33.2%) were collected from HLCs, 1423 (27.9%) from CDC light traps, 1635 (32.0%) from PSCs, and only 350 (6.9%) from pit shelters (PSs). Of these, 57.2% (n = 2915) female Anopheles mosquitoes were collected indoors using CDC light traps (CDC-LTs), human landing catches (HLCs), and pyrethrum spray catches (PSCs), while 38.2% (n = 2183) were collected outdoors using human landing collection (HLC), CDC light traps (CDC-LTs), and artificial pit shelters (PSs). Molecular identification to the species level showed that among the 530 An. gambiae s.l. samples analyzed using PCR, 96.03% (509) were An. arabiensis, and 3.97% (21) were unidentified species. The biting peak was found to be from 22:00 to 00:00 h for An. arabiensis. However, their activity decreased sharply after 23:00 to 00:00 h. The distribution of knockdown resistance genes in the tested specimens of An. arabiensis consisted of 1.4% (n = 3) heterozygous resistant (RS), 17.9% (n = 38) homozygous resistant (RR), and 80.7% (n = 171) homozygous susceptible (SS) genotypes. A higher proportion of Anopheles mosquitoes analyzed for blood meal analysis had a human blood meal origin at 13.1% (n = 47), followed by bovine at 8.9% (n = 32) and mixed at 5.8% (n = 21). Conclusions: The dominant malaria vector species was Anopheles arabiensis in the study area with a higher human blood meal origin. The Kdr gene was confirmed in the tested An. arabiensis, indicating that an alternative insecticide class should be used in the study area.

Background: Necrotizing soft tissue infections (NSTIs) are high-morbidity and high-mortality conditions that particularly affect comorbid patients. Previous Australian cohorts had limited numbers of patients within them; however, due to geographical, social and climate factors, North Queensland has significantly higher presentations than most of the country.

Methods: We have completed a retrospective cohort study between 2002 and 2012 and 2014 and 2024 of patients with ICD codes and documented clinical histories consistent with NSTI who presented to a single tertiary centre.

Results: 213 patients were identified. There was a 14% mortality rate, and common comorbidities were diabetes, smoking, high BMI and high ethanol use. Patients were likely to present with vital signs within the normal range and high inflammatory markers. Of the patients, 51% identified as First Nations, an incidence rate 88 times higher than all other ethnicities put together. First Nations patients were younger (51.78 vs. 55.74 years, p = 0.02), had higher rates of diabetes (86% vs. 34%, p ≤ 0.001), shorter times spent in ICU (6.77 days vs. 10.1 days, p = 0.03), higher average time to theatre (57.7 h vs. 35.3 h, p = 0.03) but a comparable mortality rate (13.9% vs. 13.3%, p ≥ 0.99) Conclusions: This study helps us to better understand NSTI in the Australian setting as a basis for further research.

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