Transactions of The Royal Society of Tropical Medicine and Hygiene最新文献

Background: Anisakis simplex is a parasitic zoonosis associated with consuming raw or undercooked fish. Despite its global relevance, data from Africa are scarce. This study assessed the seroprevalence and risk factors of A. simplex infection among primary schoolchildren (PSC) in Makoko, an urban slum in Lagos, Nigeria.

Methods: A cross-sectional study was conducted from November 2013 to March 2014 involving 196 PSC from three government schools. Serodiagnosis was performed using enzyme-linked immunosorbent assay (ELISA) with recombinant Ani s 1 and Ani s 7 allergens. Stool samples were examined for soil-transmitted helminths (STHs) using the Kato-Katz method. Structured questionnaires gathered demographic and dietary information.

Results: The overall seroprevalence of A. simplex infection was 12.25%. No significant association was found with gender or raw fish consumption. However, parental education and occupation influenced seropositivity. Interestingly, co-infection with STHs was inversely associated with A. simplex seropositivity. ELISA demonstrated high specificity with minimal cross-reactivity to STHs.

Conclusions: This study provides the first seroepidemiological data on A. simplex in Nigerian children. Public health interventions, particularly fish-handling education, are warranted. Further research is needed to understand the clinical relevance of A. simplex sensitization in African settings.

Background: Leprosy relapse remains a challenge to Brazil's elimination efforts, particularly in regions where Mycobacterium leprae persists in the environment. While multidrug therapy (MDT) is effective, patients exposed to ongoing transmission may develop reinfections over time. This study investigates whether proximity to pilgrimage sites influences leprosy relapse in the Cariri region.

Methods: Leprosy relapses in the Cariri region (2010-2022) were georeferenced based on patients' residences. A geostatistical model assessed relapse proximity to pilgrimage sites, classifying cases (2-18 km) and controls (18-102 km) by spatial dependence. Logistic regression assessed relapse odds near pilgrimage sites, comparing reinfections (≥5 y) to insufficient therapy (<5 y), adjusted for age, gender, cure outcome, disease severity and patient mobility.

Results: A total of 337 leprosy relapses were identified across 45 municipalities in the Cariri region. Spatial analysis indicated that individuals living near pilgrimage sites had nearly twice the odds of experiencing a relapse ≥5 y after MDT treatment (OR=1.76, 95% CI 1.09 to 2.85), supporting the hypothesis that pilgrimage sites may act as transmission hotspots.

Conclusions: Leprosy elimination in Brazil requires context-dependent measures. Pilgrimage sites, where individuals seek healing but may contribute to transmission, should be prioritized for active surveillance and targeted interventions.

Background: Few attempts have been made to explore the drug-resistant tuberculosis (DR-TB) outcomes and associated factors among underprivileged communities. This study aimed to determine DR-TB treatment outcomes and associated factors in the Saharia tribal group (TGs), a community with a high TB burden in Madhya Pradesh, India.

Methods: TB cases were detected through active case finding and were treated under the National Tuberculosis Elimination Programme. All the patients who were initiated on DR-TB treatment and had outcomes at the end of treatment were included in the study. The DR-TB treatment outcomes and associated factors were recorded.

Findings: Of 323 patients included in the analysis, 216 patients (66.8%) had successful treatment outcomes, including 70 (21.7%) who were cured and another 146 (45.2%) who completed treatment. Among the rest, 36 (11.1%) died, 66 (20.4%) were lost to follow-up and 5 (1.5%) had treatment failure. A total of 83% of patients were rifampicin resistant (RR)/multidrug resistant (MDR).

Conclusions: Although the program's recommended target of >75% could not be achieved, the treatment success rate in the study is still admirable in a hard-to-reach high-TB-risk tribal area. The findings show that with community-based approaches, favourable treatment outcomes can be achieved in DR-TB patients from resource-poor settings.

Background: Climate change projections impact dengue transmission in tropical regions, creating diverse and complex public health challenges. The aim of this study was to project future seasonal dengue incidence in a large tropical urban area of Brazil, where dengue is endemic, by systematically analyzing climatic and dengue case time series.

Methods: An epidemiological dengue model was developed using time series analysis techniques and forced with statistical downscaling from various Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models based on Shared Socioeconomic Pathway (SSP) scenarios for the late twenty-first century (2071-2100). The ecological time-series investigation analyzed 193 618 dengue cases from January 2008 to December 2018. Statistical downscaling transformed low-resolution Global Climate Models' outputs into high-resolution data, based on a 30-y climate baseline.

Results: The results indicated significant climate changes in seasonal temperature and precipitation by the end of the century. Under both SSP2-4.5 and SSP5-8.5 scenarios, substantial increases in dengue cases are projected during current low-incidence months, resulting in a reduced seasonality of dengue.

Conclusions: The findings represent considerable challenges for future public health systems, which may face sustained high levels of dengue incidence throughout the year.

Background: Melioidosis is a potentially life-threatening disease caused by Burkholderia pseudomallei. It is endemic in Southeast Asia and northern Australia and is increasingly distributed in other tropical and subtropical regions. Fast and accurate detection of B. pseudomallei is crucial for initiating prompt and effective treatment.

Methods: Loop-mediated isothermal amplification (LAMP) using hydroxynaphthol blue (HNB) for visual detection has been developed and evaluated to detect B. pseudomallei.

Results: The assay amplified B. pseudomallei TTSS1-orf2 at 63°C with a 60-min reaction and no cross-amplification was observed. The detection limit was 1.85×102 fg/µl of B. pseudomallei DNA or 2.08×102 CFU/ml of B. pseudomallei spiked in blood, sputum and urine samples. Clinical evaluation using 191 residual specimens revealed 100% negative agreement in detecting 48 of 49 culture-positive samples. Overall, the sensitivity, specificity, accuracy, positive predictive value and negative predictive value were 97.96%, 100%, 99.48%, 100% and 99.30%, respectively, while the κ index showed substantial agreement with the culture method (κ=0.99).

Conclusions: This LAMP assay demonstrated good performance, with easy operation and low cost for the rapid detection of B. pseudomallei. It has the potential to be an alternative molecular tool for the early diagnosis of melioidosis in clinical settings.

As part of a regional initiative to enhance epidemic preparedness, the Dominican Republic became one of 16 national hubs in the Artificial Intelligence for Pandemic and Epidemic Preparedness and Response Network. This article outlines the early steps taken to introduce responsible artificial intelligence into public health practice by developing local capacity, predictive surveillance tools and ethical governance strategies. Drawing on implementation experiences within the country's health institutions and communities, this article highlights practical lessons and operational insights. These findings support broader discussions on equity-focused digital innovation and provide a replicable model for low- and middle-income countries seeking to strengthen their readiness for future health threats.

Background: Hepatitis A virus (HAV) typically causes asymptomatic infection, especially in children <6 y of age. New Caledonia has low HAV endemicity, but a surge in cases between 2018 and 2022 prompted an analysis of epidemiological and virological features.

Methods: A retrospective study analysed confirmed HAV cases (2018-2022), examining demographics, hospitalisations and alanine aminotransferase (ALT) levels. Phylogenetic analysis was conducted on isolated strains.

Results: In mid-2018, imported cases from Vanuatu triggered the outbreak. Higher incidence rates were observed in the Loyalty Islands, particularly Maré Island, with subsequent spread to other areas. From 2018 to 2022, 672 cases were identified, with a median age of 13 y. Children <6 y of age accounted for 8.9% of cases, those ages 6-14 y for 54.2% and individuals ≥15 y for 36.9%. Hospitalisation occurred in 32.3% of cases. ALT levels were higher in hospitalised patients (p<0.001), but children <5 y of age had lower ALT levels overall. HAV genotyping from 16 available sera revealed subgenotype IA strains, with 14 of them linked to Vanuatu.

Conclusions: The outbreak, triggered by imported strains from Vanuatu, was facilitated by environmental and infrastructural vulnerabilities. It highlights the need for improved vaccination, especially for travellers, and the critical role of water management in preventing future outbreaks. This also underscores the importance of tracking viral circulation in the Pacific region.

Background: Understanding the prevalence, characteristics, diagnosis and management of headaches associated with neurocysticercosis (NCC) is essential for optimizing patient care.

Methods: This systematic review and meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We examined case reports, case series and cohort studies that explored headaches in NCC patients. The review protocol was registered in PROSPERO (CRD42024530164).

Results: A total of 53 isolated NCC cases presenting with headache and 8 cohort studies were included. Severe or progressive headaches, often resembling migraines, were most prevalent (35.2%). Brain parenchymal cysts were the most frequently observed lesion type (39.6%), followed by ventricular cysts (28.3%). Treatment primarily consisted of cysticidal therapy (66.2%), with surgical intervention required in 25.4% of cases. The majority of patients (96.2%) experienced clinical improvement. The meta-analysis addressed three key questions. Patients with primary headaches exhibited a significantly higher prevalence of calcified NCC (odds ratio [OR] 2.82, I2=0%). Likewise, primary headaches were more common in individuals with calcified NCC (OR 2.82, I2=0%). However, headache frequency (mean difference=1.93, I2=86%) and severity (mean difference=4.45, I2=99%) did not differ significantly.

Conclusions: Brain parenchymal cysts, particularly ring or disk-enhancing colloidal cysts, may present with new-onset headaches mimicking primary headache syndromes. Our meta-analysis indicates a significant association between calcified NCC and primary headaches, but no substantial differences were found in headache frequency or severity.

Background: Leprosy remains a significant public health challenge despite diagnostic advances.

Methods: This cross-sectional study evaluated the social and clinical characteristics of 302 patients treated at a reference outpatient clinic in northeastern Brazil (2010-2019).

Results: Men more frequently presented with multibacillary disease and disabilities than women. These clinical characteristics in men were associated with higher rates of alcohol consumption and hunting. No evidence was found for an association between diagnostic delays and disease severity.

Conclusions: This study underscores that social determinants may contribute to worse disease outcomes in men, highlighting the need for targeted policies.

Dengue fever remains a significant public health challenge, particularly in tropical and subtropical regions. With millions affected each year and the increasing prevalence of the disease due to urbanisation and climate change, effective management strategies are crucial. The incorporation of artificial intelligence (AI) in healthcare presents transformative possibilities for the management of dengue fever. AI-driven systems can improve disease surveillance by analyzing extensive volumes of epidemiological, environmental, and socio-behavioral data to identify early warning indicators and forecast outbreak trends. Enhanced diagnostic instruments driven by AI algorithms can expedite and refine case identification, especially in resource-constrained environments. Moreover, AI can enhance targeted vector control tactics by pinpointing high-risk areas and optimizing the implementation of preventive measures. AI can optimize resource allocation in healthcare institutions. These applications have the potential to substantially alleviate the burden of dengue fever, enhance patient outcomes, and fortify health system resilience. As AI technologies progress, their influence in public health is expected to grow, facilitating creative, data-driven strategies that correspond with the United Nations Sustainable Development Goals (SDGs) to enhance global health equity and disease prevention. Continued research, collaboration, and community engagement will be crucial to realising the full potential of AI in addressing this pressing public health challenge.