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Fulltext Field testing of a lightweight, inexpensive, and customisable 3D-printed mosquito light trap in the UK

Hoshi T, Brugman VA, Sato S, Ant T, Tojo B, Masuda G, et al.

Sci Rep, 2019 08 06;9(1):11412.
PMID: 31388090 DOI: 10.1038/s41598-019-47511-y

Mosquito surveillance is a fundamental component of planning and evaluating vector control programmes. However, logistical and cost barriers can hinder the implementation of surveillance, particularly in vector-borne disease-endemic areas and in outbreak scenarios in remote areas where the need is often most urgent. The increasing availability and reduced cost of 3D printing technology offers an innovative approach to overcoming these challenges. In this study, we assessed the field performance of a novel, lightweight 3D-printed mosquito light trap baited with carbon dioxide (CO2) in comparison with two gold-standard traps, the Centers for Disease Control and Prevention (CDC) light trap baited with CO2, and the BG Sentinel 2 trap with BG-Lure and CO2. Traps were run for 12 nights in a Latin square design at Rainham Marshes, Essex, UK in September 2018. The 3D-printed trap showed equivalent catch rates to the two commercially available traps. The 3D-printed trap designs are distributed free of charge in this article with the aim of assisting entomological field studies across the world.
Fulltext Recent Incidence of Human Malaria Caused by Plasmodium knowlesi in the Villages in Kudat Peninsula, Sabah, Malaysia: Mapping of The Infection Risk Using Remote Sensing Data

Sato S, Tojo B, Hoshi T, Minsong LIF, Kugan OK, Giloi N, et al.

Int J Environ Res Public Health, 2019 08 16;16(16).
PMID: 31426380 DOI: 10.3390/ijerph16162954

Plasmodium knowlesi (Pk) is a malaria parasite that naturally infects macaque monkeys in Southeast Asia. Pk malaria, the zoonosis transmitted from the infected monkeys to the humans by Anopheles mosquito vectors, is now a serious health problem in Malaysian Borneo. To create a strategic plan to control Pk malaria, it is important to estimate the occurrence of the disease correctly. The rise of Pk malaria has been explained as being due to ecological changes, especially deforestation. In this research, we analysed the time-series satellite images of MODIS (MODerate-resolution Imaging Spectroradiometer) of the Kudat Peninsula in Sabah and created the "Pk risk map" on which the Land-Use and Land-Cover (LULC) information was visualised. The case number of Pk malaria of a village appeared to have a correlation with the quantity of two specific LULC classes, the mosaic landscape of oil palm groves and the nearby land-use patches of dense forest, surrounding the village. Applying a Poisson multivariate regression with a generalised linear mixture model (GLMM), the occurrence of Pk malaria cases was estimated from the population and the quantified LULC distribution on the map. The obtained estimations explained the real case numbers well, when the contribution of another risk factor, possibly the occupation of the villagers, is considered. This implies that the occurrence of the Pk malaria cases of a village can be predictable from the population of the village and the LULC distribution shown around it on the map. The Pk risk map will help to assess the Pk malaria risk distributions quantitatively and to discover the hidden key factors behind the spread of this zoonosis.
Short-term associations of PM10 attributed to biomass burning with respiratory and cardiovascular hospital admissions in Peninsular Malaysia

Tajudin MABA, Madaniyazi L, Seposo X, Sahani M, Tobías A, Latif MT, et al.

Int J Epidemiol, 2024 Jun 12;53(4).
PMID: 39096096 DOI: 10.1093/ije/dyae102

BACKGROUND: Biomass burning (BB) is a major source of air pollution and particulate matter (PM) in Southeast Asia. However, the health effects of PM smaller than 10 µm (PM10) originating from BB may differ from those of other sources. This study aimed to estimate the short-term association of PM10 from BB with respiratory and cardiovascular hospital admissions in Peninsular Malaysia, a region often exposed to BB events.
METHODS: We obtained and analyzed daily data on hospital admissions, PM10 levels and BB days from five districts from 2005 to 2015. We identified BB days by evaluating the BB hotspots and backward wind trajectories. We estimated PM10 attributable to BB from the excess of the moving average of PM10 during days without BB hotspots. We fitted time-series quasi-Poisson regression models for each district and pooled them using meta-analyses. We adjusted for potential confounders and examined the lagged effects up to 3 days, and potential effect modification by age and sex.
RESULTS: We analyzed 210 960 respiratory and 178 952 cardiovascular admissions. Almost 50% of days were identified as BB days, with a mean PM10 level of 53.1 µg/m3 during BB days and 40.1 µg/m3 during normal days. A 10 µg/m3 increment in PM10 from BB was associated with a 0.44% (95% CI: 0.06, 0.82%) increase in respiratory admissions at lag 0-1, with a stronger association in adults aged 15-64 years and females. We did not see any significant associations for cardiovascular admissions.
CONCLUSIONS: Our findings suggest that short-term exposure to PM10 from BB increased the risk of respiratory hospitalizations in Peninsular Malaysia.
Fulltext Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries

Huy NT, Chico RM, Huan VT, Shaikhkhalil HW, Uyen VNT, Qarawi ATA, et al.

PLoS One, 2021;16(12):e0258348.
PMID: 34936646 DOI: 10.1371/journal.pone.0258348

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave.
METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training.
RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors.
INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type.
Fulltext Anxiety and its risk factors among non-Japanese residents living in Japan undergoing COVID-19 situation: A cross-sectional survey

Luu MN, Imoto A, Matsuo Y, Huy NT, Qarawi A, Alhady STM, et al.

PLoS One, 2024;19(3):e0280144.
PMID: 38489310 DOI: 10.1371/journal.pone.0280144

INTRODUCTION: In the context of collective efforts taken in Japan to control the spread of COVID-19, the state of emergency and social distancing have caused a negative impact on the mental health of all residents, including foreign communities in Japan. This study aimed to evaluate the level of anxiety and its associated factors among non-Japanese residents residing in Japan during the COVID-19 pandemic.
METHODS: A web-based survey in 13 languages was conducted among non-Japanese residents living in Japan during the COVID-19 situation. The State-Trait Anxiety Inventory assessed the level of anxiety-State (STAI-S) scores prorated from its six-item version. The multivariable logistic regression using the Akaike Information Criterion (AIC) method was performed to identify the associated factors of anxiety among participants.
RESULTS: From January to March 2021, we collected 392 responses. A total of 357 valid responses were analyzed. 54.6% of participants suffered from clinically significant anxiety (CSA). In multivariable logistic model analysis, the CSA status or the high level of anxiety was associated with three factors, including having troubles/difficulties in learning or working, decreased sleep duration, and decreased overall physical health (p<0.05).
CONCLUSION: Our study suggests several possible risk factors of anxiety among non-Japanese residents living in Japan undergoing the COVID-19 pandemic, including the troubles or difficulties in learning or working, the decrease in sleep duration, and the decrease in overall physical health.