Dengue virus type 3 genotype III (DENV-3/III) is widely distributed in most dengue-endemic regions. It emerged in Malaysia in 2008 and autochthonously spread in the midst of endemic DENV-3/I circulation. The spread, however, was limited and the virus did not cause any major outbreak. Spatiotemporal distribution study of DENV-3 over the period between 2005 and 2011 revealed that dengue cases involving DENV-3/III occurred mostly in areas without pre-existing circulating DENV-3. Neutralisation assays performed using sera of patients with the respective infection showed that the DENV-3/III viruses can be effectively neutralised by sera of patients with DENV-3 infection (50% foci reduction neutralisation titres (FRNT50) > 1300). Sera of patients with DENV-1 infection (FRNT50 ⩾ 190), but not sera of patients with DENV-2 infection (FRNT50 ⩽ 50), were also able to neutralise the virus. These findings highlight the possibility that the pre-existing homotypic DENV-3 and the cross-reacting heterotypic DENV-1 antibody responses could play a role in mitigating a major outbreak involving DENV-3/III in the Klang Valley, Malaysia.
Parasitic infections have been reported to be relatively common among the Southeast Asian labourers in Taiwan. This study, conducted in 1992-6, was designed to determine the temporal changes of the prevalence. Faecal specimens were examined by the formalin-ethyl acetate sedimentation technique and blood samples screened using the quantitative buffy coat technique and confirmed by Giemsa stained blood smear. The overall prevalence of intestinal parasitic infections was 10.3%. The annual prevalence decreased from 33.3% in 1992-3 to 4.6% in 1995-6. The Thai (12.0%) and Indonesian (11.1%) had a higher prevalence than the Malaysian (6.7%) and Filipinos (5.9%). Opisthorchis viverrini was the most important parasite in the Thai and Trichuris trichiura in the remaining groups. Moreover, no blood parasites were found in the labourers. The dramatic temporal decline in the intestinal parasitic infections suggests that limiting the entry of infected persons, periodic follow-ups, and immediate treatment of sporadic cases are necessary in preventing transmission of non-indigenous parasites through large population change.
Novel Coronavirus (2019-nCoV [SARS-COV-2]) was detected in humans during the last week of December 2019 at Wuhan city in China, and caused 24 554 cases in 27 countries and territories as of 5 February 2020. The objective of this study was to estimate the risk of transmission of 2019-nCoV through human passenger air flight from four major cities of China (Wuhan, Beijing, Shanghai and Guangzhou) to the passengers' destination countries. We extracted the weekly simulated passengers' end destination data for the period of 1-31 January 2020 from FLIRT, an online air travel dataset that uses information from 800 airlines to show the direct flight and passengers' end destination. We estimated a risk index of 2019-nCoV transmission based on the number of travellers to destination countries, weighted by the number of confirmed cases of the departed city reported by the World Health Organization (WHO). We ranked each country based on the risk index in four quantiles (4th quantile being the highest risk and 1st quantile being the lowest risk). During the period, 388 287 passengers were destined for 1297 airports in 168 countries or territories across the world. The risk index of 2019-nCoV among the countries had a very high correlation with the WHO-reported confirmed cases (0.97). According to our risk score classification, of the countries that reported at least one Coronavirus-infected pneumonia (COVID-19) case as of 5 February 2020, 24 countries were in the 4th quantile of the risk index, two in the 3rd quantile, one in the 2nd quantile and none in the 1st quantile. Outside China, countries with a higher risk of 2019-nCoV transmission are Thailand, Cambodia, Malaysia, Canada and the USA, all of which reported at least one case. In pan-Europe, UK, France, Russia, Germany and Italy; in North America, USA and Canada; in Oceania, Australia had high risk, all of them reported at least one case. In Africa and South America, the risk of transmission is very low with Ethiopia, South Africa, Egypt, Mauritius and Brazil showing a similar risk of transmission compared to the risk of any of the countries where at least one case is detected. The risk of transmission on 31 January 2020 was very high in neighbouring Asian countries, followed by Europe (UK, France, Russia and Germany), Oceania (Australia) and North America (USA and Canada). Increased public health response including early case recognition, isolation of identified case, contract tracing and targeted airport screening, public awareness and vigilance of health workers will help mitigate the force of further spread to naïve countries.
Dengue infection in China has increased dramatically in recent years. Guangdong province (main city Guangzhou) accounted for more than 94% of all dengue cases in the 2014 outbreak. Currently, there is no existing effective vaccine and most efforts of control are focused on the vector itself. This study aimed to evaluate different dengue management strategies in a region where this disease is emerging. This work was done by establishing a dengue simulation model for Guangzhou to enable the testing of control strategies aimed at vector control and vaccination. For that purpose, the computer-based dengue simulation model (DENSiM) together with the Container-Inhabiting Mosquito Simulation Model (CIMSiM) has been used to create a working dengue simulation model for the city of Guangzhou. In order to achieve the best model fit against historical surveillance data, virus introduction scenarios were run and then matched against the actual dengue surveillance data. The simulation model was able to predict retrospective outbreaks with a sensitivity of 0.18 and a specificity of 0.98. This new parameterisation can now be used to evaluate the potential impact of different control strategies on dengue transmission in Guangzhou. The knowledge generated from this research would provide useful information for authorities regarding the historic patterns of dengue outbreaks, as well as the effectiveness of different disease management strategies.
Little is known about Clostridium difficile infection (CDI) in Asia. The aims of our study were to explore (i) the prevalence, risk factors and molecular epidemiology of CDI and colonization in a tertiary academic hospital in North-Eastern Peninsular Malaysia; (ii) the rate of carriage of C. difficile among the elderly in the region; (iii) the awareness level of this infection among the hospital staffs and students. For stool samples collected from hospital inpatients with diarrhea (n = 76) and healthy community members (n = 138), C. difficile antigen and toxins were tested by enzyme immunoassay. Stool samples were subsequently analyzed by culture and molecular detection of toxin genes, and PCR ribotyping of isolates. To examine awareness among hospital staff and students, participants were asked to complete a self-administered questionnaire. For the hospital and community studies, the prevalence of non-toxigenic C. difficile colonization was 16% and 2%, respectively. The prevalence of CDI among hospital inpatients with diarrhea was 13%. Out of 22 C. difficile strains from hospital inpatients, the toxigenic ribotypes 043 and 017 were most common (both 14%). In univariate analysis, C. difficile colonization in hospital inpatients was significantly associated with greater duration of hospitalization and use of penicillin (both P < 0·05). Absence of these factors was a possible reason for low colonization in the community. Only 3% of 154 respondents answered all questions correctly in the awareness survey. C. difficile colonization is prevalent in a Malaysian hospital setting but not in the elderly community with little or no contact with hospitals. Awareness of CDI is alarmingly poor.
Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) - dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients' quality of life. Integrating PK/PD-EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.
Nipah virus (NiV) is an emerging bat-borne pathogen. It was first identified 20 years ago in Malaysia and has since caused outbreaks in other parts of South and Southeast Asia. It causes severe neurological and respiratory disease which is highly lethal. It is highly infectious and spreads in the community through infected animals or other infected people. Different strains of the virus show differing clinical and epidemiological features. Rapid diagnosis and implementation of infection control measures are essential to contain outbreaks. A number of serological and molecular diagnostic techniques have been developed for diagnosis and surveillance. Difficulties in diagnosis and management arise when a new area is affected. The high mortality associated with infection and the possibility of spread to new areas has underscored the need for effective management and control. However, no effective treatment or prophylaxis is readily available, though several approaches show promise. Given the common chains of transmission from bats to humans, a One Health approach is necessary for the prevention and control of NiV infection.
We aimed to reparameterize and validate an existing dengue model, comprising an entomological component (CIMSiM) and a disease component (DENSiM) for application in Malaysia. With the model we aimed to measure the effect of importation rate on dengue incidence, and to determine the potential impact of moderate climate change (a 1 °C temperature increase) on dengue activity. Dengue models (comprising CIMSiM and DENSiM) were reparameterized for a simulated Malaysian village of 10 000 people, and validated against monthly dengue case data from the district of Petaling Jaya in the state of Selangor. Simulations were also performed for 2008-2012 for variable virus importation rates (ranging from 1 to 25 per week) and dengue incidence determined. Dengue incidence in the period 2010-2012 was modelled, twice, with observed daily weather and with a 1 °C increase, the latter to simulate moderate climate change. Strong concordance between simulated and observed monthly dengue cases was observed (up to r = 0·72). There was a linear relationship between importation and incidence. However, a doubling of dengue importation did not equate to a doubling of dengue activity. The largest individual dengue outbreak was observed with the lowest dengue importation rate. Moderate climate change resulted in an overall decrease in dengue activity over a 3-year period, linked to high human seroprevalence early on in the simulation. Our results suggest that moderate reductions in importation with control programmes may not reduce the frequency of large outbreaks. Moderate increases in temperature do not necessarily lead to greater dengue incidence.