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D-dimer, a byproduct of cross-linked fibrin degradation, arises during the fibrinolysis process, breaking down blood clots in circulation. This systematic review and meta-analysis aimed to synthesize evidence of D-dimer alteration in people with malaria, including variations in disease severity. The systematic review was registered in PROSPERO with registration number CRD42024528245. Searches were performed in EMBASE, Scopus, MEDLINE, PubMed, Nursing & Allied Health Premium, and Journals@Ovid on March 25, 2024, to identify original studies that reported D-dimer in patients with Plasmodium infections. The methodological quality of the included studies was assessed using the Joanna Briggs Institute critical appraisal tools. Thematic synthesis and meta-analysis were carried out to synthesize the findings of the included studies. A total of 24 studies were included in the review out of 1,115 records identified. According to the evaluated studies, patients with Plasmodium infections had higher D-dimer levels. A meta-analytic evaluation of D-dimer levels between patients with and without Plasmodium infections revealed a significant elevation of D-dimer in patients with infection, with high heterogeneity (SMD = 2.11, 95% CI = 0.59; 3.64, P = 0.007, I² = 98%, 6 studies, 1,418 participants, random-effects model). However, no significant alterations in D-dimer levels were observed following the comparison between patients with severe and uncomplicated malaria, also with high heterogeneity (SMD = 2.54, 95% CI = -1.60; 6.68, P = 0.23, I² = 99%, 3 studies, 595 participants). The findings suggested that malaria patients have significantly higher D-dimer levels compared to non-malarial individuals. However, there was no significant difference in D-dimer levels between severe and uncomplicated malaria cases. These results highlight the potential of D-dimer as a biomarker for Plasmodium infections, but its clinical utility requires further validation. Future studies should prioritize standardizing D-dimer measurement methods, including assay types, threshold values, and sample types, to ensure consistent and reliable application in clinical settings. Additionally, large, multicentric cohorts are needed to establish robust guidelines for incorporating D-dimer into malaria management practices. Further research should also explore the role of D-dimer in the pathogenesis of Plasmodium infections to deepen our understanding of their clinical significance., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Dengue, a zoonotic viral disease transmitted by Aedes mosquitoes, poses a significant public health concern throughout the Lao People's Democratic Republic (Lao PDR). This study aimed to describe spatial-temporal patterns and quantify the effects of environmental and climate variables on dengue transmission at the district level. The dengue data from 2015 to 2020 across 148 districts of Lao PDR were obtained from the Lao PDR National Center for Laboratory and Epidemiology (NCLE). The association between monthly dengue occurrences and environmental and climate variations was investigated using a multivariable Zero-inflated Poisson regression model developed in a Bayesian framework. The study analyzed a total of 72,471 dengue cases with an incidence rate of 174 per 100,000 population. Each year, incidence peaked from June to September and a large spike was observed in 2019. The Bayesian spatio-temporal model revealed a 9.1% decrease (95% credible interval [CrI] 8.9%, 9.2%) in dengue incidence for a 0.1 unit increase in monthly normalized difference vegetation index at a 1-month lag and a 5.7% decrease (95% CrI 5.3%, 6.2%) for a 1 cm increase in monthly precipitation at a 6-month lag. Conversely, dengue incidence increased by 43% (95% CrI 41%, 45%) for a 1 °C increase in monthly mean temperature at a 3-month lag. After accounting for covariates, the most significant high-risk spatial clusters were detected in the southern regions of Lao PDR. Probability analysis highlighted elevated trends in 45 districts, emphasizing the importance of targeted control strategies in high-risk areas. This research underscores the impact of climate and environmental factors on dengue transmission, emphasizing the need for proactive public health interventions tailored to specific contexts in Lao PDR., (© 2024. The Author(s).)

Malaria has complex interactions with host physiology, including alterations in cortisol levels. Cortisol, a key hormone in the stress response, is known to be dysregulated in various infectious diseases. This systematic review and meta-analysis aimed to elucidate the relationship between Plasmodium infection and cortisol levels, shedding light on the intricate interplay between the parasite and the host's endocrine system. The methodological protocol for assessing cortisol levels in malaria patients was registered in PROSPERO (CRD42024496578), a widely recognized international prospective register of systematic reviews. This registration ensures transparency and minimizes the risk of bias in our research. A comprehensive search strategy was employed across major databases, including Embase, PubMed, Scopus, and Medline, to include studies that reported cortisol levels in infected patients. The qualitative synthesis was undertaken to synthesize the difference in cortisol levels between malaria-infected and uninfected individuals. The meta-analysis employed the random effects model in the quantitative synthesis to calculate the effect estimate. The review included a total of 20 studies, with a substantial number conducted in Africa, followed by Asia and South America. Most included studies (13/20, 65%) reported higher cortisol levels in infected patients than in uninfected patients. The meta-analysis confirmed significantly higher cortisol levels in infected patients compared to uninfected individuals (P < 0.0001, standardized mean difference (SMD): 1.354, 95% confidence interval: 0.913 to 1.795, I 2 : 88.3%, across 15 studies). Notably, the method for cortisol measurement and the type of blood sample used (serum or plasma) were significant moderators in the analysis, indicating that these factors may influence the observed relationship between Plasmodium infection and cortisol levels. The systematic review and meta-analysis confirmed that Plasmodium infection is associated with increased cortisol levels, highlighting the intricate relationship between the disease and the host stress response. These findings underscore the potential of cortisol as a supplementary biomarker for understanding the pathophysiological impact of malaria. By providing insights into the stress-related mechanisms of malaria, this comprehensive understanding can inform future research and potentially enhance disease management and treatment strategies, particularly in regions heavily burdened by malaria., (© 2024. The Author(s).)

Albumin, a key protein in human blood plasma, has been linked to various health conditions. However, its association with malaria, particularly in assessing disease severity, remains inadequately understood. This comprehensive systematic review and meta-analysis aimed to elucidate the relationship between albumin levels and malaria severity. A comprehensive literature search was conducted across multiple databases, including Embase, Scopus, PubMed, MEDLINE, Ovid, and Google Scholar, to identify studies examining albumin levels in malaria patients. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Data were pooled using a random-effects model, and heterogeneity was assessed using I 2 statistics. Subgroup and meta-regression analyses were performed based on publication year, study location, and Plasmodium species. A total of 37 studies were included in this review. The thematic synthesis indicated that albumin levels in malaria patients varied significantly based on geographical location. A meta-analysis of 28 studies found that albumin levels were significantly lower in malaria patients compared with non-malarial controls (P < 0.001, standardized mean differences [SMD] = -2.23, 95% CI - 3.25 to - 1.20, I 2 : 98%, random effects model, 28 studies). Additionally, subgroup analysis revealed variations in albumin levels based on geographical location and Plasmodium species. Regarding the association with disease severity, thematic synthesis showed that severe malaria cases generally had decreased albumin levels across various regions. However, one Brazilian study reported higher albumin levels in severe cases. A separate meta-analysis of five studies found significantly lower albumin levels in patients experiencing severe malaria relative to those with less severe forms of the disease (P < 0.001, SMD = -0.66, 95% CI - 1.07 to - 0.25), I 2 : 73%, random effects model, 5 studies). This study underscores the clinical significance of albumin as a potential biomarker for Plasmodium infection and the severity of malaria. The findings suggest that albumin level monitoring could be crucial in managing malaria patients, especially in assessing disease severity and tailoring treatment approaches. Additional studies are required to investigate the underlying mechanisms driving these associations and validate the clinical utility of albumin levels in malaria patient management., (© 2024. The Author(s).)

Reports indicate that Plasmodium infections influence methemoglobin levels. However, findings have been inconclusive or have varied across different geographic and demographic contexts. This systematic review and meta-analysis aimed to consolidate existing data regarding the association between Plasmodium infections and alterations in methemoglobin levels related to the severity of the infection. A comprehensive literature search of several databases, including Ovid, ProQuest, Embase, Scopus, MEDLINE, and PubMed, was conducted to identify relevant studies that examined methemoglobin levels in patients with malaria. Qualitative synthesis and meta-analysis of the pooled standardized mean difference were conducted to synthesize the differences in methemoglobin levels between: (1) patients with malaria and those without malaria and (2) patients with severe malaria and those with uncomplicated malaria based on various themes including publication year, study design, study area, Plasmodium species, age group, symptomatic status, severity status, and method of malaria detection. Of the 1846 studies that were initially identified from the main databases and additional searches on Google Scholar, 10 studies met the eligibility criteria and were selected for this review. The systematic review distinctly highlighted an association between malaria and elevated methemoglobin levels, an observation consistent across diverse geographical regions and various Plasmodium species. Furthermore, the meta-analysis confirmed this by demonstrating increased methemoglobin levels in patients with malaria compared to those without malaria (P < 0.001, Hedges' g 2.32, 95% CI 1.36-3.29, I 2 97.27, 8 studies). Moreover, the meta-analysis found elevated methemoglobin levels in patients with severe malaria compared to those with uncomplicated malaria (P < 0.001, Hedges' g 2.20, 95% CI 0.82-3.58, I 2 96.20, 5 studies). This systematic review and meta-analysis revealed increased methemoglobin levels in patients with P. falciparum and P. vivax infections, with a notable association between elevated methemoglobin levels and severe malaria. Future research should focus on elucidating the specific mechanisms by which changes in methemoglobin levels are related to infections by P. falciparum and P. vivax, particularly in terms of severity, and how these alterations could potentially impact patient management and treatment outcomes., (© 2024. The Author(s).)

The common cold is a leading cause of morbidity and contributes significantly to the health costs in Bhutan. The study utilized multivariate Zero-inflated Poisson regression in a Bayesian framework to identify climatic variability and spatial and temporal patterns of the common cold in Bhutan. There were 2,480,509 notifications of common cold between 2010 and 2018. Children aged < 15 years were twice (95% credible interval [CrI] 2.2, 2.5) as likely to get common cold than adults, and males were 12.4% (95 CrI 5.5%, 18.7%) less likely to get common cold than females. A 10 mm increase in rainfall lagged one month, and each 1 °C increase of maximum temperature was associated with a 5.1% (95% CrI 4.2%, 6.1%) and 2.6% (95% CrI 2.3%, 2.8%) increase in the risk of cold respectively. An increase in elevation of 100 m and 1% increase in relative humidity lagged three months were associated with a decrease in risk of common cold by 0.1% (95% CrI 0.1%, 0.2%) and 0.3% (95% CrI 0.2%, 0.3%) respectively. Seasonality and spatial heterogeneity can partly be explained by the association of common cold to climatic variables. There was statistically significant residual clustering after accounting for covariates. The finding highlights the influence of climatic variables on common cold and suggests that prioritizing control strategies for acute respiratory infection program to subdistricts and times of the year when climatic variables are associated with common cold may be an effective strategy., (© 2022. The Author(s).)

In 2020, 77% of malaria cases in the Americas were concentrated in Venezuela, Brazil, and Colombia. These countries are characterized by a heterogeneous malaria landscape and malaria hotspots. Furthermore, the political unrest in Venezuela has led to significant cross-border population movement. Hence, the aim of this study was to describe spatial patterns and identify significant climatic drivers of malaria transmission along the Venezuela-Brazil-Guyana border, focusing on Bolivar state, Venezuela and Roraima state, Brazil. Malaria case data, stratified by species from 2016 to 2018, were obtained from the Brazilian Malaria Epidemiology Surveillance Information System, the Guyana Vector Borne Diseases Program, the Venezuelan Ministry of Health, and civil society organizations. Spatial autocorrelation in malaria incidence was explored using Getis-Ord (Gi*) statistics. A Poisson regression model was developed with a conditional autoregressive prior structure and posterior parameters were estimated using the Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. There were 685,498 malaria cases during the study period. Plasmodium vivax was the predominant species (71.7%, 490,861). Malaria hotspots were located in eight municipalities along the Venezuela and Guyana international borders with Brazil. Plasmodium falciparum increased by 2.6% (95% credible interval [CrI] 2.1%, 2.8%) for one meter increase in altitude, decreased by 1.6% (95% CrI 1.5%, 2.3%) and 0.9% (95% CrI 0.7%, 2.4%) per 1 cm increase in 6-month lagged precipitation and each 1 °C increase of minimum temperature without lag. Each 1 °C increase of 1-month lagged maximum temperature increased P. falciparum by 0.6% (95% CrI 0.4%, 1.9%). P. vivax cases increased by 1.5% (95% CrI 1.3%, 1.6%) for one meter increase in altitude and decreased by  1.1% (95% CrI 1.0%, 1.2%) and 7.3% (95% CrI 6.7%, 9.7%) for each 1 cm increase of precipitation lagged at 6-months and 1 °C increase in minimum temperature lagged at 6-months. Each 1°C increase of two-month lagged maximum temperature increased P. vivax by 1.5% (95% CrI 0.6%, 7.1%). There was no significant residual spatial clustering after accounting for climatic covariates. Malaria hotspots were located along the Venezuela and Guyana international border with Roraima state, Brazil. In addition to population movement, climatic variables were important drivers of malaria transmission in these areas., (© 2022. The Author(s).)

Globally, cross-border importation of malaria has become a challenge to malaria elimination. The border areas between Brazil and Venezuela have experienced high numbers of imported cases due to increased population movement and migration out of Venezuela. This study aimed to identify risk factors for imported malaria and delineate imported malaria hotspots in Roraima, Brazil and Bolivar, Venezuela between 2016 and 2018. Data on malaria surveillance cases from Roraima, Brazil and Bolivar, Venezuela from 2016 to 2018 were obtained from national surveillance systems: the Brazilian Malaria Epidemiology Surveillance Information System (SIVEP-Malaria), the Venezuelan Ministry of Health and other non-government organizations. A multivariable logistic regression model was used to identify the risk factors for imported malaria. Spatial autocorrelation in malaria incidence was explored using Getis-Ord (Gi*) statistics. During the study period, there were 11,270 (24.3%) and 4072 (0.7%) imported malaria cases in Roraima, Brazil and Bolivar, Venezuela, respectively. In the multivariable logistic regression for Roraima, men were 28% less likely to be an imported case compared to women (Adjusted Odds Ratio [AOR] = 0.72; 95% confidence interval [CI] 0.665, 0.781). Ages 20-29 and 30-39 were 90% (AOR = 1.90; 95% CI 1.649, 2.181) and 54% (AOR = 1.54; 95% CI 1.331, 1.782) more likely to be an imported case compared to the 0-9 year age group, respectively. Imported cases were 197 times (AOR = 197.03; 95% CI 175.094, 221.712) more likely to occur in miners than those working in agriculture and domestic work. In Bolivar, cases aged 10-19 (AOR = 1.75; 95% CI 1.389, 2.192), 20-29 (AOR = 2.48; 95% CI 1.957, 3.144), and 30-39 (AOR = 2.29; 95% CI 1.803, 2.913) were at higher risk of being an imported case than those in the 0-9 year old group, with older age groups having a slightly higher risk compared to Roraima. Compared to agriculture and domestic workers, tourism, timber and fishing workers (AOR = 6.38; 95% CI 4.393, 9.254) and miners (AOR = 7.03; 95% CI 4.903, 10.092) were between six and seven times more likely to be an imported case. Spatial analysis showed the risk was higher along the international border in the municipalities of Roraima, Brazil. To achieve malaria elimination, cross-border populations in the hotspot municipalities will need targeted intervention strategies tailored to occupation, age and mobility status. Furthermore, all stakeholders, including implementers, policymakers, and donors, should support and explore the introduction of novel approaches to address these hard-to-reach populations with the most cost-effective interventions., (© 2022. The Author(s).)

Pneumonia is one of the top 10 diseases by morbidity in Bhutan. This study aimed to investigate the spatial and temporal trends and risk factors of childhood pneumonia in Bhutan. A multivariable Zero-inflated Poisson regression model using a Bayesian Markov chain Monte Carlo simulation was undertaken to quantify associations of age, sex, altitude, rainfall, maximum temperature and relative humidity with monthly pneumonia incidence and to identify the underlying spatial structure of the data. Overall childhood pneumonia incidence was 143.57 and 10.01 per 1000 persons over 108 months of observation in children aged < 5 years and 5-14 years, respectively. Children < 5 years or male sex were more likely to develop pneumonia than those 5-14 years and females. Each 1 °C increase in maximum temperature was associated with a 1.3% (95% (credible interval [CrI] 1.27%, 1.4%) increase in pneumonia cases. Each 10% increase in relative humidity was associated with a 1.2% (95% CrI 1.1%, 1.4%) reduction in the incidence of pneumonia. Pneumonia decreased by 0.3% (CrI 0.26%, 0.34%) every month. There was no statistical spatial clustering after accounting for the covariates. Seasonality and spatial heterogeneity can partly be explained by the association of pneumonia risk to climatic factors including maximum temperature and relative humidity., (© 2021. The Author(s).)

Cholangiocarcinoma (CCA) is a serious health challenge with low survival prognosis. The liver fluke, Opisthorchis viverrini, plays a role in the aetiology of CCA, through hepatobiliary abnormalities: liver mass (LM), bile duct dilation, and periductal fibrosis (PDF). A population-based CCA screening program, the Cholangiocarcinoma Screening and Care Program, operates in Northeast Thailand. Hepatobiliary abnormalities were identified through ultrasonography. A multivariate zero-inflated, Poisson regression model measured associations between hepatobiliary abnormalities and covariates including age, sex, distance to water resource, and history of O. viverrini infection. Geographic distribution was described using Bayesian spatial analysis methods. Hepatobiliary abnormality prevalence was 38.7%; highest in males aged > 60 years (39.8%). PDF was most prevalent (20.1% of males). The Standardized Morbidity Ratio (SMR) for hepatobiliary abnormalities was highest in the lower and upper parts of the Northeast region. Hepatobiliary abnormalities specifically associated with CCA were also more common in males and those aged over 60 years and distributed along the Chi, Mun, and Songkram Rivers. Our findings demonstrated a high risk of hepatobiliary disorders in Northeast Thailand, likely associated with infection caused by O. viverrini. Screening for CCA and improvement of healthcare facilities to provide better treatment for CCA patients should be prioritized in these high-risk areas.

At a time when Bhutan is on the verge of malaria elimination, the aim of this study was to identify malaria clusters at high geographical resolution and to determine its association with local environmental characteristics. Malaria cases from 2006-2014 were obtained from the Vector-borne Disease Control Program under the Ministry of Health, Bhutan. A Zero-Inflated Poisson multivariable regression model with a conditional autoregressive (CAR) prior structure was developed. Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling was used to estimate posterior parameters. A total of 2,062 Plasmodium falciparum and 2,284 Plasmodium vivax cases were reported during the study period. Both species of malaria showed seasonal peaks with decreasing trend. Gender and age were not associated with the transmission of either species of malaria. P. falciparum increased by 0.7% (95% CrI: 0.3%, 0.9%) for a one mm increase in rainfall, while climatic variables (temperature and rainfall) were not associated with P. vivax. Insecticide treated bed net use and residual indoor insecticide coverage were unaccounted for in this study. Hot spots and clusters of both species were isolated in the central southern part of Bhutan bordering India. There was significant residual spatial clustering after accounting for climate and demographic variables.

Cholangiocarcinoma (CCA) is a malignant neoplasm of the biliary tract. Thailand reports the highest incidence of CCA in the world. The aim of this study was to map the distribution of CCA and identify spatial disease clusters in Northeast Thailand. Individual-level data of patients with histopathologically confirmed CCA, aggregated at the sub-district level, were obtained from the Cholangiocarcinoma Screening and Care Program (CASCAP) between February 2013 and December 2017. For analysis a multivariate Zero-inflated, Poisson (ZIP) regression model was developed. This model incorporated a conditional autoregressive (CAR) prior structure, with posterior parameters estimated using Bayesian Markov chain Monte Carlo (MCMC) simulation with Gibbs sampling. Covariates included in the models were age, sex, normalized vegetation index (NDVI), and distance to water body. There was a total of 1,299 cases out of 358,981 participants. CCA incidence increased 2.94 fold (95% credible interval [CrI] 2.62-3.31) in patients >60 years as compared to ≤60 years. Males were 2.53 fold (95% CrI: 2.24-2.85) more likely to have CCA when compared to females. CCA decreased with a 1 unit increase of NDVI (Relative Risk =0.06; 95% CrI: 0.01-0.63). When posterior means were mapped spatial clustering was evident after accounting for the model covariates. Age, sex and environmental variables were associated with an increase in the incidence of CCA. When these covariates were included in models the maps of the posterior means of the spatially structured random effects demonstrated evidence of spatial clustering.