Floods can lead to direct economic and property losses and result not only in physical injuries and deaths but
also in psychological trauma. Post-traumatic stress disorder (PTSD) is a commonly used indicator to evaluate
psychological injuries after disaster. This study aimed to determine the relationship between PTSD prevalence
and related perceived severity of post flood impact by economical, non-economical and flood status severity
domains besides relevant socio-demographic factors according to gender specific analysis. This cross-sectional
study was conducted among community in Kampung Hulu Takir, Kuala Terengganu, Malaysia in 2015 two
weeks after flood. It included a total of 98 males and 110 females aged 18 years and above. Data was
collected by interview-guided questionnaire to determine the prevalence of PTSD. SPSS version 21.0 was used
for analysis of the relationship between socio demographic factors, perceived economic, non-economic and
flood severity with PTSD. Finally chi square test was used to assess the predictors of PTSD according to
gender. The prevalence of PTSD was 9.2% in males and 10.9% in females, giving a total of 10.1%. Significantly
higher prevalence of PTSD was found in severely perceived economic and flood impact categories (33.3% and
23.8% in males; 23.8 % and 37.5% in females) and giving in overall 44.0% and 31.3 % respectively. Effective
PTSD management strategies targeting females post flood victims who severely perceived economically and
nature flood impact should be implemented in order to prevent further consequences of PTSD.
Aedes mosquito-borne Dengue morbidity is predominantly high in the tropics and subtropics regions. Dengue is also a
public health problem in Malaysia since the first epidemic in 1973. Reducing the vector population and personal
protection still plays an important role in dengue prevention and control. With the information of community’s dengue
knowledge, attitude and practices (KAP), the authorities could construct evidence-based, community- empowered vector
control program. Upon the understanding of the value of baseline data, a cross-sectional study was carried out in dengue
hotspot areas in Seberang Takir using universal sampling. The study results showed that 54.6% of the population had high
level of knowledge, 18.6% had good attitude and 91.7% were performing good practices against Dengue infection. After
adjusting confounding variables, age and educational levels of respondents, knowledge as well as attitude were found to
be significant associated factors for having good practice against Dengue. The study findings provide the need for further
information to undertake a holistic approach which is in need of community participation and cooperatio
During the initial phase of the coronavirus disease 2019 (COVID-19) pandemic, there was a critical need to create a valid and reliable screening and surveillance for university staff and students. Consequently, 11 medical experts participated in this cross-sectional study to judge three risk categories of either low, medium, or high, for all 1536 possible combinations of 11 key COVID-19 predictors. The independent experts' judgement on each combination was recorded via a novel dashboard-based rating method which presented combinations of these predictors in a dynamic display within Microsoft Excel. The validated instrument also incorporated an innovative algorithm-derived deduction for efficient rating tasks. The results of the study revealed an ordinal-weighted agreement coefficient of 0.81 (0.79 to 0.82, p-value < 0.001) that reached a substantial class of inferential benchmarking. Meanwhile, on average, the novel algorithm eliminated 76.0% of rating tasks by deducing risk categories based on experts' ratings for prior combinations. As a result, this study reported a valid, complete, practical, and efficient method for COVID-19 health screening via a reliable combinatorial-based experts' judgement. The new method to risk assessment may also prove applicable for wider fields of practice whenever a high-stakes decision-making relies on experts' agreement on combinations of important criteria.