IgE antibody responses in cerebrospinal fluids relate to the brain pathologic injury of hosts with Angiostrongylus cantonensis infection.

BACKGROUND: The immunoglobulin E (IgE) response to Angiostrongylus cantonensis infection increases in the host. This study analyzed the IgG and IgE responses detected in different body fluids of A. cantonensis-infected mice. METHODS: BALB/c (high susceptibility), CBA (medium), and C57BL/6 and C57BL/10 (resistance) strain mice were used in this study. The levels of IgM, IgG, and IgE in the serum and cerebrospinal fluid (CSF) from infected mice were compared. A. cantonensis-reactive antigens from BALB/c and C57BL/6 mice CSF were also analyzed. RESULTS: Antibodies against fifth-stage larvae (L5) antigens increased in mice CSF, particularly IgE, relate to worm rejection and the susceptibility of different mouse strains. The increased IgE level in BALB/c mice CSF is lower than that from others, suggesting IgE response in brain is more important than that in serum. Anti-L5 and anti-excretory/secretory (ES) antigen IgE and IgG responses in CSF were analyzed. In addition, the antibody-dependent eosinophil-mediated cytotoxicity induced by anti-excretory/secretory (ES) antigen antibodies may be the reason of severe brain inflammation in infected BALB/c mice. IgE and IgG antibodies against a 105 kDa protein of L5 antigen was detected at week 3 post-infection in C57BL/6 mice and week 5 post-infection in BALB/c mice. We suggest that 105 kDa protein is related with the antibody response of A. cantonensis-infected mice. CONCLUSION: We found that IgE antibodies in mice CSF against L5 antigens related to worm rejection in mice brains. This study may help to identify specific angiostrongyliasis markers that can be applied for clinical diagnosis and treatment in future.

Climate change and mortality rates of COPD and asthma: A global analysis from 2000 to 2018.

BACKGROUND: Climate change plays a significant role in global health threats, particularly with respiratory diseases such as chronic obstructive pulmonary disease (COPD) and asthma, but the long-term global-scale impact of climate change on these diseases' mortality remains unclear. OBJECTIVE: This study aims to investigate the impact of climate change on the age-standardized mortality rates (ASMR) of COPD and asthma at national levels. METHODS: We used Global Burden of Disease (GBD) data of ASMR of COPD and asthma from 2000 to 2018. The climate change index was represented as the deviance percentage of temperature (DPT) and relative humidity (DPRH), calculated based on 19-year temperature and humidity averages. Annual temperature, RH, and fine particulate matter (PM2.5) levels in 185 countries/regions were obtained from ERA5 and the OECD's environmental statistics database. General linear mixed-effect regression models were used to examine the associations between climate change with the log of ASMR (LASMR) of COPD and asthma. RESULTS: After adjusting for annual PM2.5, SDI level, smoking prevalence, and geographical regions, a 0.26% increase in DPT was associated with decreases of 0.016, 0.017, and 0.014 per 100,000 people in LASMR of COPD and 0.042, 0.046, and 0.040 per 100,000 people in LASMR of asthma for both genders, males, and females. A 2.68% increase in DPRH was associated with increases of 0.009 and 0.011 per 100,000 people in LASMR of COPD. We observed a negative association of DPT with LASMR for COPD in countries/regions with temperatures ranging from 3.8 to 29.9 °C and with LASMR for asthma ranging from -5.3-29.9 °C. However, we observed a positive association of DPRH with LASMR for both COPD and asthma in the RH range of 41.2-67.2%. CONCLUSION: Climate change adaptation and mitigation could be crucial in reducing the associated COPD and asthma mortality rates, particularly in regions most vulnerable to temperature and humidity fluctuations.

Corrigendum: Predicting Plasmodium knowlesi transmission risk across Peninsular Malaysia using machine learning-based ecological niche modeling approaches.

[This corrects the article DOI: 10.3389/fmicb.2023.1126418.].

An Integrative Explainable Artificial Intelligence Approach to Analyze Fine-Scale Land-Cover and Land-Use Factors Associated with Spatial Distributions of Place of Residence of Reported Dengue Cases.

Dengue fever is a prevalent mosquito-borne disease that burdens communities in subtropical and tropical regions. Dengue transmission is ecologically complex; several environmental conditions are critical for the spatial and temporal distribution of dengue. Interannual variability and spatial distribution of dengue transmission are well-studied; however, the effects of land cover and use are yet to be investigated. Therefore, we applied an explainable artificial intelligence (AI) approach to integrate the EXtreme Gradient Boosting and Shapley Additive Explanation (SHAP) methods to evaluate spatial patterns of the residences of reported dengue cases based on various fine-scale land-cover land-use types, Shannon's diversity index, and household density in Kaohsiung City, Taiwan, between 2014 and 2015. We found that the proportions of general roads and residential areas play essential roles in dengue case residences with nonlinear patterns. Agriculture-related features were negatively associated with dengue incidence. Additionally, Shannon's diversity index showed a U-shaped relationship with dengue infection, and SHAP dependence plots showed different relationships between various land-use types and dengue incidence. Finally, landscape-based prediction maps were generated from the best-fit model and highlighted high-risk zones within the metropolitan region. The explainable AI approach delineated precise associations between spatial patterns of the residences of dengue cases and diverse land-use characteristics. This information is beneficial for resource allocation and control strategy modification.

Predicting Plasmodium knowlesi transmission risk across Peninsular Malaysia using machine learning-based ecological niche modeling approaches.

The emergence of potentially life-threatening zoonotic malaria caused by Plasmodium knowlesi nearly two decades ago has continued to challenge Malaysia healthcare. With a total of 376 P. knowlesi infections notified in 2008, the number increased to 2,609 cases in 2020 nationwide. Numerous studies have been conducted in Malaysian Borneo to determine the association between environmental factors and knowlesi malaria transmission. However, there is still a lack of understanding of the environmental influence on knowlesi malaria transmission in Peninsular Malaysia. Therefore, our study aimed to investigate the ecological distribution of human P. knowlesi malaria in relation to environmental factors in Peninsular Malaysia. A total of 2,873 records of human P. knowlesi infections in Peninsular Malaysia from 1st January 2011 to 31st December 2019 were collated from the Ministry of Health Malaysia and geolocated. Three machine learning-based models, maximum entropy (MaxEnt), extreme gradient boosting (XGBoost), and ensemble modeling approach, were applied to predict the spatial variation of P. knowlesi disease risk. Multiple environmental parameters including climate factors, landscape characteristics, and anthropogenic factors were included as predictors in both predictive models. Subsequently, an ensemble model was developed based on the output of both MaxEnt and XGBoost. Comparison between models indicated that the XGBoost has higher performance as compared to MaxEnt and ensemble model, with AUCROC values of 0.933 ± 0.002 and 0.854 ± 0.007 for train and test datasets, respectively. Key environmental covariates affecting human P. knowlesi occurrence were distance to the coastline, elevation, tree cover, annual precipitation, tree loss, and distance to the forest. Our models indicated that the disease risk areas were mainly distributed in low elevation (75-345 m above mean sea level) areas along the Titiwangsa mountain range and inland central-northern region of Peninsular Malaysia. The high-resolution risk map of human knowlesi malaria constructed in this study can be further utilized for multi-pronged interventions targeting community at-risk, macaque populations, and mosquito vectors.

Updating the Insecticide Resistance Status of Aedes aegypti and Aedes albopictus in Asia: A Systematic Review and Meta-Analysis.

BACKGROUND: Aedes aegypti and Aedes albopictus are two important vectors of several important arboviruses, including the dengue, chikungunya, and Zika viruses. Insecticide application is an important approach to reduce vector abundance during Aedes spp.-borne outbreaks in the absence of effective vaccines and treatments. However, insecticide overuse can result in the development of resistance, and careful monitoring of resistance markers is required. METHODS: This meta-analysis and systematic review explored the spatial and temporal patterns of insecticide resistance in Asia from 2000 to 2021. PubMed, Scopus, EbscoHost, and Embase were used to enhance the search capability. The random-effects model was applied for the 94 studies that met our inclusion criteria for qualitative synthesis and meta-analysis. RESULTS: Four major insecticides were studied (malathion, dichlorodiphenyltrichloroethane, permethrin, and deltamethrin). Dichlorodiphenyltrichloroethane resistance rates were high in both Ae. aegypti and Ae. albopictus (68% and 64%, respectively). Conversely, malathion resistance was less prevalent in Ae. aegypti (3%), and deltamethrin resistance was less common in Ae. albopictus (2%). Ae. aegypti displayed consistently high resistance rates (35%) throughout the study period, whereas the rate of insecticide resistance in Ae. albopictus increased from 5% to 12%. The rates of the major kdr mutations F1534C, V1016G, and S989P were 29%, 26%, and 22%, respectively. CONCLUSIONS: Insecticide resistance in both Ae. aegypti and Ae. albopictus is widespread in Asia, although the rates vary by country. Continuous monitoring of the resistance markers and modification of the control strategies will be important for preventing unexpected outbreaks. This systematic review and meta-analysis provided up-to-date information on insecticide resistance in dengue-endemic countries in Asia.

Exposure to ambient air pollutants with kidney function decline in chronic kidney disease patients.

Chronic kidney disease (CKD) has been a global public health problem with many adverse outcomes, but data are lacking regarding the relationship between air pollutants and risk of renal progression in patients with CKD. This study was to investigate whether 1-year average exposure to ambient air pollutants -CO, NO, NO2, SO2, O3, PM2.5, and PM10-is related to renal function deterioration among patients with CKD. A total of 5301 CKD patients were included in this study between October 2008 and February 2016. To estimate each patient's exposure to ambient air pollution, we used the 24-h ambient air pollution concentration monitoring data collected one year prior to renal progression or their last renal function assessment. Renal progression was considered when estimated glomerular filtration rate (eGFR) decreased more than 25% from the baseline eGFR. Cox proportional hazard regression was performed to calculate hazard ratios (HRs). Among 5301 patients with CKD, 1813 (34.20%) developed renal progression during the 30.48 ± 14.99-month follow-up. Patients with the highest quartile exposure to CO [HR = 1.53 (95% CI: 1.24, 1.88)], NO [HR = 1.38 (95% CI: 1.11, 1.71)], NO2 [HR = 1.63 (95% CI: 1.36, 1.97)], SO2 [HR = 2.27 (95% CI: 1.83, 2.82)], PM2.5 [HR = 7.58 (95% CI: 5.97, 9.62)], and PM10 [HR = 3.68 (95% CI: 2.84, 4.78)] had a significantly higher risk of renal progression than those with the lowest quartile exposure. In the multipollutant model, the analyses yielded to similar results. These results reinforce the importance of measures to mitigate air pollution and strategies to prevent worsening of kidney function in patients with CKD. One-year high exposure to ambient CO, NO, NO2, SO2, PM2.5, and PM10 is significantly associated with deteriorated kidney function in patients with CKD among Taiwanese adults.

Linguistic Pattern-Infused Dual-Channel Bidirectional Long Short-term Memory With Attention for Dengue Case Summary Generation From the Program for Monitoring Emerging Diseases-Mail Database: Algorithm Development Study.

BACKGROUND: Globalization and environmental changes have intensified the emergence or re-emergence of infectious diseases worldwide, such as outbreaks of dengue fever in Southeast Asia. Collaboration on region-wide infectious disease surveillance systems is therefore critical but difficult to achieve because of the different transparency levels of health information systems in different countries. Although the Program for Monitoring Emerging Diseases (ProMED)-mail is the most comprehensive international expert-curated platform providing rich disease outbreak information on humans, animals, and plants, the unstructured text content of the reports makes analysis for further application difficult. OBJECTIVE: To make monitoring the epidemic situation in Southeast Asia more efficient, this study aims to develop an automatic summary of the alert articles from ProMED-mail, a huge textual data source. In this paper, we proposed a text summarization method that uses natural language processing technology to automatically extract important sentences from alert articles in ProMED-mail emails to generate summaries. Using our method, we can quickly capture crucial information to help make important decisions regarding epidemic surveillance. METHODS: Our data, which span a period from 1994 to 2019, come from the ProMED-mail website. We analyzed the collected data to establish a unique Taiwan dengue corpus that was validated with professionals' annotations to achieve almost perfect agreement (Cohen κ=90%). To generate a ProMED-mail summary, we developed a dual-channel bidirectional long short-term memory with attention mechanism with infused latent syntactic features to identify key sentences from the alerting article. RESULTS: Our method is superior to many well-known machine learning and neural network approaches in identifying important sentences, achieving a macroaverage F1 score of 93%. Moreover, it can successfully extract the relevant correct information on dengue fever from a ProMED-mail alerting article, which can help researchers or general users to quickly understand the essence of the alerting article at first glance. In addition to verifying the model, we also recruited 3 professional experts and 2 students from related fields to participate in a satisfaction survey on the generated summaries, and the results show that 84% (63/75) of the summaries received high satisfaction ratings. CONCLUSIONS: The proposed approach successfully fuses latent syntactic features into a deep neural network to analyze the syntactic, semantic, and contextual information in the text. It then exploits the derived information to identify crucial sentences in the ProMED-mail alerting article. The experiment results show that the proposed method is not only effective but also outperforms the compared methods. Our approach also demonstrates the potential for case summary generation from ProMED-mail alerting articles. In terms of practical application, when a new alerting article arrives, our method can quickly identify the relevant case information, which is the most critical part, to use as a reference or for further analysis.

Toxoplasma gondii infection: seroprevalence and associated risk factors for women of childbearing age in Osun State, Nigeria.

Toxoplasmosis is a common parasitic infection caused by an obligate intracellular protozoan, Toxoplasma gondii. Prevalence and risk factors of T. gondii infection in women of childbearing age in Osun State, Nigeria are unknown. This study was aimed to determine the seroprevalence and potential risk factors in acquiring T. gondii infection by women of childbearing age in Osun State, Nigeria. A community-based cross-sectional study was conducted from May 2019 to December 2019 in childbearing age women. Sera of 415 women aged 18-49 years randomly selected were collected and analyzed by enzyme-linked immunosorbent assay (ELISA) test. A questionnaire survey was administered for all study participants to collect socio-demographic and risk factors data. The study revealed that the overall seroprevalence of T. gondii infection was 76.63%, which comprised 6.02% positivity for anti-T. gondii IgM (25/415), 44.10% for IgG (183/415) and 26.51% for IgG plus IgM (110/415). Seroprevalence of IgM antibodies to T. gondii (6.02%) suggested recent infections. Women residing in rural communities and women of Islam religion showed significant association with anti-T. gondii seropositivity (p < 0.05). Residence location and women who are of Islam religion are risk factors to acquire T. gondii infection. Hence, health education and awareness on the disease and its transmission to women of childbearing age group in general and pregnant women in particular should be created during antenatal follow up to reduce the risk of T. gondii infection in pregnant women.

Epidemiologic Study of Enterobius vermicularis Infection among Schoolchildren in the Republic of Marshall Islands.

The prevalence and risk factors of Enterobius vermicularis (pinworm) infection among primary schoolchildren (PSC) in the Marshall Islands remain unknown; thus, investigation on the status of pinworm infection rate is necessary to establish baseline data. After parents'/guardians' consent, a total of 346 children (179 boys and 167 girls) participated in this study. Individual's perianal area and thumbs were inspected by using the Scotch tape technique and cellophane tape method, respectively. For each child, demographic and risk factor data were collected by a structured questionnaire and statistically analyzed. The overall prevalence of pinworm infection was 12.14% (42/346). Univariate analysis indicated significant differences in PSC who live in an urban area compared to those who live in the rural area (p=0.01). Multivariate analysis still found that PSC who live in the rural area had higher chances to acquire pinworm infection. However, no risk factors were identified to be associated with personal hygiene, sibling number, and parent's educational level or occupation. Nevertheless, a pinworm-like egg was detected on the thumb of one male participant. Children living in the rural area and thumb-sucking behavior are two of the important risk factors of transmitting pinworm infection in the PSC in the Marshall Islands. We suggested an urgent and continuous provision of adequate hygienic sensitization in the school and the community.

High variability in model performance of Google relative search volumes in spatially clustered COVID-19 areas of the USA.

OBJECTIVE: Incorporating spatial analyses and online health information queries may be beneficial in understanding the role of Google relative search volume (RSV) data as a secondary public health surveillance tool during pandemics. This study identified coronavirus disease 2019 (COVID-19) clustering and defined the predictability performance of Google RSV models in clustered and non-clustered areas of the USA. METHODS: Getis-Ord General and local G statistics were used to identify monthly clustering patterns. Monthly country- and state-level correlations between new daily COVID-19 cases and Google RSVs were assessed using Spearman's rank correlation coefficients and Poisson regression models for January-December 2020. RESULTS: Huge clusters involving multiple states were found, which resulted from various control measures in each state. This demonstrates the importance of state-to-state coordination in implementing control measures to tackle the spread of outbreaks. Variability in Google RSV model performance was found among states and time periods, possibly suggesting the need to use different frameworks for Google RSV data in each state. Moreover, the sign of correlation can be utilized to understand public responses to control and preventive measures, as well as in communicating risk. CONCLUSION: COVID-19 Google RSV model accuracy in the USA may be influenced by COVID-19 transmission dynamics, policy-driven community awareness and past outbreak experiences.

Effects of soil lead exposure and land use characteristics on neurodevelopment among children under 3 years of age in northern Taiwan.

Lead (Pb) exposure increases the risks of neurodevelopmental disorders in children. Child-specific activities and land use scenarios may lead to elevated opportunities for Pb exposure through the soil. Therefore, we investigated hair and fingernail Pb concentrations among young children in northern Taiwan, in relation to soil Pb pollution and land use characteristics. We also explored the effect of the Pb exposure burden and land use scenarios on neurobehavioral development. In total, 139 healthy children under 3 years of age were recruited in October 2011 to April 2014. Pb levels in hair and fingernail samples were determined using an inductively coupled plasma/mass spectrometer. Pb concentrations in soils and land use types surrounding the children's homes were accessed by a geographic information system to identify any associations with hair Pb levels. The Bayley Scales of Infant and Toddler Development (Bayley-III) were used to evaluate the cognitive, language, and motor development of the children. A multivariable regression model was performed to assess the effects of soil Pb levels and land-use status on Pb exposure in children, as well as associations of Pb exposure and land-use scenarios with neurodevelopmental abilities. Geometric mean Pb concentrations in hair, fingernails, and soil were 2.9 ± 4.8 µg/g, 0.8 ± 5.1 µg/g, and 20.8 ± 4.3 mg/kg, respectively. The multivariable analysis indicated that soil Pb concentrations and green areas around residences had potential links with Pb exposure among children in northern Taiwan. Hair Pb concentrations were negatively associated with expressive language scores. Soil Pb exposure was positively associated with hair Pb concentrations. Land use types around the children's homes in northern Taiwan were associated with their neurodevelopment. Increased green areas were negatively associated with hair Pb concentrations. Living near a highway may have had negative impacts on gross motor scores. A healthy residence can avoid potential health risks for children during their early life.

Long-term exposure to ozone and sulfur dioxide increases the incidence of type 2 diabetes mellitus among aged 30 to 50 adult population.

AIMS/HYPOTHESIS: Worldwide, the information regarding the associations between long-term exposure to ozone (O3) and sulfur dioxide (SO2) and the development of type 2 diabetes remains scarce, especially in Asia. This study aimed to investigate the long-term effects of exposure to ambient O3 and SO2 on the incidence of type 2 diabetes with consideration of other air pollutants in Taiwanese adults aged 30 to 50 years. METHODS: A total of 6,426,802 non-diabetic participants aged between 30 and 50 years old were obtained from the National Health Insurance Research Database between 2005 and 2016. Incident type 2 diabetes was the main diagnosis at medical visits. Air quality data were provided by the Taiwan Environmental Protection Administration. The air pollutant concentrations for each participant were estimated using the ordinary kriging method to interpolate daily concentrations of O3, SO2, carbon monoxide (CO), nitrogen dioxide (NO2), suspended fine particles (with an aerodynamic diameter less than 2.5 µm; PM2.5), and suspended particles (with an aerodynamic diameter less than 10 µm; PM10) in residential districts across Taiwan. Six-year average concentrations of pollutants were calculated from January 1, 2005 to December 31, 2010, and data were categorized into quartiles. We performed Cox regression models to analyze the long-term effects of exposure to O3 and SO2 on the incidence of type 2 diabetes. RESULTS: The hazard ratio (HR) for the incidence of diabetes per each interquartile range (IQR) increase in ozone exposure (3.30 ppb) was 1.058 (95% confidence interval (CI): 1.053, 1.064) and 1.011 (95% CI: 1.007, 1.015) for SO2 exposure (1.77 ppb) after adjusting for age, sex, socioeconomic status, urbanization level, temperature, humidity, and chronic comorbidities (Model 3). Furthermore, for every 3.30 ppb increase of O3, the HR for incident type 2 diabetes was 1.093 (95% CI: 1.087, 1.100) after controlling factors shown in Model 3 plus SO2 and PM2.5. On the other hand, for every 1.77 ppb increase of SO2, the HR for incident type 2 diabetes was 1.073 (95% CI: 1.068, 1.079) after controlling factors shown in Model 3 plus NO2 and PM2.5. CONCLUSIONS: Long-term exposure to ambient O3 and SO2 was associated with a higher risk of developing type 2 diabetes for Taiwanese population. Exposure to O3 and SO2 may play a role in the adult early-onset type 2 diabetes.

Lower risk of primary Sjogren's syndrome in patients with dengue virus infection: a nationwide cohort study in Taiwan.

The data concerning the association between dengue viruses (DV) infection and autoimmune diseases (ADs) remain unclear and are scarce. This nationwide population-based cohort study assessed the risk of ADs among patients with DV infection. We analyzed Taiwanese medical data from the Registry of the National Notifiable Disease Reporting System of Taiwan's Centers for Disease Control between 1998 and 2015 and identified patients with DV infection. From the entire general population data in the National Health Insurance Research Database, we randomly selected a comparison cohort that was individual matching by age, sex, residence, and index date. We analyzed the risk of ADs using a Cox proportional hazards regression model stratified by sex, age, and residence. We enrolled 29,365 patients with DV infection (50.68% men; mean age, 44.13 years) and 117,460 age-, sex-, and residence-matched controls in the present study. The incidence rates of organ-specific ADs were nonsignificantly higher in the DV cohort than in the non-DV control cohort. An approximately 70% lower risk of primary Sjogren syndrome (pSS) was evident in the DV cohort than in the non-DV control cohort with an adjusted hazard ratio of 0.30 (95% confidence interval 0.13-0.67) after adjusting for comorbidities in matched design. By contrast, the other systemic ADs were nonsignificantly lower in the DV cohort than in the non-DV control cohort. This nationwide long-term cohort study demonstrated that patients with DV infection had a lower risk of primary Sjogren syndrome than those without DV infection. Key Points • This retrospective, longitudinal cohort observational study shows that patients with DV infection had a lower risk of pSS than those without DV infection. • The DV cohort had an approximately 70% lower risk of pSS than the control group, with a multivariate-adjusted HR of 0.30. • On the basis of this result, we contended that DV infection has a protective effect that reduces the risk of pSS.

Influence of Maternal Exposure to Malaria Social and Behavioral Change Messages and Effectiveness of Communication Media on Bed Net Use and Malaria Infection in Malawi.

BACKGROUND: Malawi is a malaria-endemic country. A national malaria communication strategy was adopted to disseminate malaria messages with the aim of improving knowledge and adoption of malaria interventions. OBJECTIVE: To examine the effect of maternal exposure to malaria messages and the medium through which such messages are delivered on insecticide-treated net (ITN) use and malaria infection among children under 5 years of age in Malawi. METHODOLOGY: Utilizing the data from the 2017 Malawi Malaria Indicator Survey, 2,055 children (aged under 5 years) and 1,886 children (aged 6-59 months) were analyzed for ITN use and malaria infection outcomes, respectively. Components of exposure to malaria messages were tested for association with ITN use and malaria infection outcomes using multiple logistic regression models. RESULTS: Children whose mothers had reported hearing any malaria-related message in the past 6 months were more likely to sleep under an ITN and less likely to have malaria infection compared with those whose mothers had not heard any malaria-related message. Region and sex of the child were effect modifiers on the relationship between exposure to any malaria-related message and malaria infection. Knowledge regarding cause or protection methods partially mediated the relationship between exposure to any malaria message and malaria infection. DISCUSSION AND CONCLUSION: Health workers were an effective communication channel. Strengthening topic-specific malaria messages and building the capacity of health workers while alternately strengthening other message outlets may prove vital for effective malaria communication.

Spatial and Temporal Analysis of Plasmodium knowlesi Infection in Peninsular Malaysia, 2011 to 2018.

The life-threatening zoonotic malaria cases caused by Plasmodium knowlesi in Malaysia has recently been reported to be the highest among all malaria cases; however, previous studies have mainly focused on the transmission of P. knowlesi in Malaysian Borneo (East Malaysia). This study aimed to describe the transmission patterns of P. knowlesi infection in Peninsular Malaysia (West Malaysia). The spatial distribution of P. knowlesi was mapped across Peninsular Malaysia using Geographic Information System techniques. Local indicators of spatial associations were used to evaluate spatial patterns of P. knowlesi incidence. Seasonal autoregressive integrated moving average models were utilized to analyze the monthly incidence of knowlesi malaria in the hotspot region from 2012 to 2017 and to forecast subsequent incidence in 2018. Spatial analysis revealed that hotspots were clustered in the central-northern region of Peninsular Malaysia. Time series analysis revealed the strong seasonality of transmission from January to March. This study provides fundamental information on the spatial distribution and temporal dynamic of P. knowlesi in Peninsular Malaysia from 2011 to 2018. Current control policy should consider different strategies to prevent the transmission of both human and zoonotic malaria, particularly in the hotspot region, to ensure a successful elimination of malaria in the future.

Effects of Malaria Interventions During Pregnancy on Low Birth Weight in Malawi.

INTRODUCTION: In malaria-endemic countries, malaria during pregnancy is associated with adverse birth outcomes, including low birth weight (i.e., <2.5 kg). However, the effects of the widely promoted and recommended approaches of intermittent preventive treatment for malaria in pregnancy and insecticide-treated nets for pregnant women on low birth weight have been insufficiently examined. This analysis investigates the independent and combined effects of intermittent preventive treatment for malaria in pregnancy and insecticide-treated nets on low birth weight among Malawian children. METHODS: Using pooled data sets from 2004, 2010, and 2015-2016 Malawi Demographic and Health Surveys, a total of 18,285 births were analyzed between August and December 2019. Binomial generalized linear regression models with a log-link function explored the associations under consideration. RESULTS: The overall low birth weight prevalence was 10.3%. Prevalence was lower in children whose mothers used adequate intermittent preventive treatment for malaria in pregnancy (adjusted prevalence ratio=0.88, 95% CI=0.79, 0.99) or used insecticide-treated nets (adjusted prevalence ratio=0.89, 95% CI=0.79, 0.99) than their respective counterparts. Low birth weight was 20.0% lower among children whose mothers adequately used both intermittent preventive treatment for malaria in pregnancy and insecticide-treated nets than those without these approaches (adjusted prevalence ratio=0.80, 95% CI=0.68, 0.93). Iron supplement consumption and survey year were significant effect modifiers on the relationship between intermittent preventive treatment for malaria in pregnancy and low birth weight. CONCLUSIONS: There were evident benefits of independent and combined use of intermittent preventive treatment for malaria in pregnancy and insecticide-treated nets on low birth weight, thereby supporting the use of these interventions during pregnancy. The reduced protective effects of intermittent preventive treatment for malaria in pregnancy over time highlight the need for innovative preventive methods against malaria in pregnancy.

Impact of Climate Variability and Abundance of Mosquitoes on Dengue Transmission in Central Vietnam.

Dengue fever is an important arboviral disease in many countries. Its incidence has increased during the last decade in central Vietnam. Most dengue studies in Vietnam focused on the northern area (Hanoi) and southern regions but not on central Vietnam. Dengue transmission dynamics and relevant environmental risk factors in central Vietnam are not understood. This study aimed to evaluate spatiotemporal patterns of dengue fever in central Vietnam and effects of climatic factors and abundance of mosquitoes on its transmission. Dengue and mosquito surveillance data were obtained from the Department of Vector Control and Border Quarantine at Nha Trang Pasteur Institute. Geographic Information System and satellite remote sensing techniques were used to perform spatiotemporal analyses and to develop climate models using generalized additive models. During 2005-2018, 230,458 dengue cases were reported in central Vietnam. Da Nang and Khanh Hoa were two major hotspots in the study area. The final models indicated the important role of Indian Ocean Dipole, multivariate El Niño-Southern Oscillation index, and vector index in dengue transmission in both regions. Regional climatic variables and mosquito population may drive dengue transmission in central Vietnam. These findings provide important information for developing an early dengue warning system in central Vietnam.

High seroprevalence of Toxocara antibodies in pregnant women attending an antenatal clinic at a university hospital in Ile-Ife, Nigeria.

BACKGROUND: Human toxocariasis is a neglected zoonotic disease and its impact on human health is underestimated. Studies investigating the occurrence of toxocariasis in pregnancy are very scarce in Nigeria. This study investigated the seroprevalence of Toxocara spp. antibodies as well as the possible risk factors in pregnant women who routinely attended an antenatal clinic in a university hospital in Ile-Ife, Osun state. METHODS: Blood samples were collected from 413 participating pregnant women between October 2017 and February 2018. Epidemiological data were obtained through a structured questionnaire. The sera were screened for anti-Toxocara IgG antibodies by western blot technique based on Toxocara canis larval excretory-secretory antigens, targeting low molecular weight bands of 24-35 kDa, specifically for T. canis infection. RESULTS: The overall seroprevalence was 92.49% (382/413). There was no significant difference in the seroprevalence rate of Toxocara spp. infection between pregnant women aged ≤30 y and those aged >30 y (91.63 vs 93.33%; OR 1.28, 95% CI 0.61 to 2.67, p=0.511). The seroprevalence rate increased with the number of miscarriages but there was no statistical significance (p>0.05). Moreover, no significant associations were found between Toxocara spp. seropositivity and other studied risk factors (p>0.05). CONCLUSION: The high seroprevalence of Toxocara spp. in pregnant Nigerian women needs comprehensive health education regarding personal hygiene and how to avoid exposure to this parasite infection.

Contextual Factors and Spatial Patterns of Childhood Malnutrition in Provinces of Burkina Faso.

BACKGROUND: Approximately 45% of all children's deaths are associated with malnutrition, and sub-Saharan Africa is hardest hit by this phenomenon. However, information on geographical variations of malnutrition in developing countries is limited. This study examined the geographical distribution and community characteristics associated with child malnutrition in Burkina Faso. DESIGN: Data from the 2011 Burkina Faso Demographic Health Survey were analyzed. A general Kriging interpolation method was used to generate spatial malnutrition patterns. The global Moran's I test was used to identify significant malnutrition spatial patterns. Generalized estimating equations (GEEs) were fitted to examine the association between community level factors and malnutrition. RESULTS: Average rates of stunting and wasting in the communities were 32.48% and 15.05%, respectively. Stunting hotspots were observed in the eastern and northeastern parts of Burkina Faso (i.e. Oudolan, Séno and Yagha, among others), while high rates of wasting were observed in the north-central part. The GEE results revealed lower stunting rates in communities with a higher percentage of households with improved sanitation. Communities with higher rates of professionally assisted births were associated with low wasting rates, while communities with higher rates of households with a low wealth index reported higher rates of wasting. CONCLUSIONS: Spatial statistical models of malnutrition prevalence are useful for indicating hotspots over wide areas and hence, for guiding intervention strategies. This study revealed significant geographical patterns and community factors associated with childhood malnutrition. These factors should be considered in future programs aimed at reducing malnutrition in Burkina Faso.