The control of dengue outbreak requires a multi-pronged effort by the various government agencies. It requires co-operation of the community in the control activities, strict adherence to existing control procedures and guidelines by health personnel, increased manpower where necessary and strengthening co-operation between various health agencies to prevent delay in instituting control measures.
A food poisoning outbreak affected 114 female Malay students staying in a religious secondary school hostel in Klang. The students developed an illness mainly characterized by abdominal pain, nausea, vomiting and giddiness. The median incubation period in this outbreak was 2.5 hours. Laboratory examination of suspected food revealed 2.3 X10^6 Bacillus cereus organisms per gram of fried noodles. B. cereus was determined as the probable cause of this outbreak and the fried. noodles the most likely vehicle for the organism. An outbreak of B. cereus food poisoning is being reported in Malaysia for the first time.
Cholera has been in existence in Sarawak for many years and since 1873 many major epidemics have occurred. The epidemics usually occur during the dry months of May, June and July and the population affected are those in coastal areas. As in other outbreaks the areas affected were those which had poor environmental sanitation, poor water supply, poor refuse disposal and indiscriminate disposal of faeces. Malays are more affected as in Peninsular Malaysia outbreaks. The classical biotype was common prior to 1961. In later years the El Tor (biotype) has been responsible for most outbreaks.
The molecular epidemiology of the virus and mapping helps understand the epidemics' evolution and apply quick control measures. This study provides genomic evidence of multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) introductions into Sri Lanka and virus evolution during circulation. Whole-genome sequences of four SARS-CoV-2 strains obtained from coronavirus disease 2019 (COVID-19) positive patients reported in Sri Lanka during March 2020 were compared with sequences from Europe, Asia, Africa, Australia and North America. The phylogenetic analysis revealed that the sequence of the sample of the first local patient collected on 10 March, who contacted tourists from Italy, was clustered with SARS-CoV-2 strains collected from Italy, Germany, France and Mexico. Subsequently, the sequence of the isolate obtained on 19 March also clustered in the same group with the samples collected in March and April from Belgium, France, India and South Africa. The other two strains of SARS-CoV-2 were segregated from the main cluster, and the sample collected from 16 March clustered with England and the sample collected on 30 March showed the highest genetic divergence to the isolate of Wuhan, China. Here we report the first molecular epidemiological study conducted on circulating SARS-CoV-2 in Sri Lanka. The finding provides the robustness of molecular epidemiological tools and their application in tracing possible exposure in disease transmission during the pandemic.
Matched MeSH terms: Disease Outbreaks/prevention & control
The response to the COVID-19 pandemic have been driven by epidemiology, health system characteristics and control measures in form of social/physical distancing. Guidance, information and best practices have been characterized by territorial thinking with concentration on national health system and social contexts. Information was to a large extent provided from global entities such as the World Health Organization (WHO), Centers for Disease Control and Prevention (CDC) and others. This bipolar response mechanism came to the detriment of regional and sub-regional levels. The development of the global pandemic was evaluated in terms of the performance of single countries without trying to reflect on possible regional or sub-regional results of similar characteristics in health system and social contexts. To have a clearer view of the issue of sub-regional similarities, we examined the WHO, Eastern Mediterranean Region. When examining the development of confirmed cases for countries in the region, we identified four different sub-groups similar in the development of the pandemic and the social distancing measure implemented. Despite the complicated situation, these groups gave space for thinking outside the box of traditional outbreaks or pandemic response. We think that this sub-regional approach could be very effective in addressing more characteristics and not geographically based analysis. Furthermore, this can be an area of additional conceptual approaches, modelling and concrete platforms for information and lessons learned exchange.
Matched MeSH terms: Disease Outbreaks/prevention & control
The author discusses some of the features of the cholera epidemic caused by El Tor vibrios in 1961-62 in the Western Pacific. The disease originated in the Celebes and spread from there to other parts of Indonesia, to Sarawak and, possibly, to Kwangtung. Hong Kong and Macau were most probably infected from Kwangtung. Subsequently the disease reached the Philippines, progressing from Manila southwards to the other islands, whence it invaded British Borneo. The El Tor epidemic did not differ clinically or epidemiologically from other cholera outbreaks observed during the past decade. The disease attacked poor, under-nourished people living under insanitary conditions. It spread along the coastline and, to a limited extent, along inland waterways. The authorities in the affected territories recommended that the quarantine regulations, sanitary measures and treatment methods used against cholera caused by the so-called "true" cholera vibrios be applied also to cholera caused by El Tor vibrios.
The horseshoe crab (Carcinoscorpius rotundicauda) is consumed by those residing near the coastal areas of Kota Marudu District in Malaysia, as it is considered a delicacy. During June to August, 2011 thirty cases of tetrodotoxin poisoning were reported from Kota Marudu District following ingestion of horseshoe crabs caught in Kota Marudu Bay. The purpose of this study is to describe this case series in order to determine risk factors to prevent further outbreaks. There were six confirmed and 24 probable cases of tetrodotoxin poisoning identified in the study area during the study period as diagnosed by clinical presentation and laboratory findings. Symptoms included dizziness (80%), circumoral and lingual numbness (80%), hand and feet numbness (63.3%), nausea and vomiting (30%) and weakness and difficulty in breathing (26.6%). Three cases (10%) died while 27 cases recovered. Forty-seven percent of the cases had onset of symptoms within 30 minutes of ingestion and 14% 31-60 minutes after ingestion of horseshoe crab meat. Urine samples were collected from the cases, while horseshoe crabs, cockles and sea water from the epidemic area were also taken for analysis. Tetrodotoxin was detected in the urine of six cases; the highest concentrations recorded were among the three cases who died. High tetrodotoxin concentrations were found in the hepatic cecum and eggs of the tested horseshoe crabs. Dinoflagellates were not detected in the sea water or cockle samples. Intensive health education was initiated quickly to stop other members of the Marudu Bay community from consuming the horseshoe crabs. This is the first documented epidemic of tetrodotoxin poisoning in Sabah.
Although individuals with Zika virus (ZIKV) antibodies were reported in Malaya in mid-1950s, entomological and human surveillance in Singapore did not identify autochthonous transmission until the outbreak of August-November, 2016. A total of 455 cases from 15 separate clusters were identified. We asked if this ZIKV outbreak increased the incidence of Guillain-Barré syndrome (GBS) and aimed to characterize these cases. Eleven GBS cases, consecutively enrolled into our prospective GBS database from onset to 4 weeks after outbreak, and six controls, comprising three GBS patients enrolled before outbreak and three non-GBS patients, were examined for evidence of recent ZIKV infection. We performed serum, urine ZIKV RT-PCR, ZIKV serology, and virus neutralization assays, accounting for cross-reaction and co-infection with dengue (DENV). We found five GBS cases with only serological evidence of recent ZIKV infection (including one ZIKV-DENV co-infection). A temporal relationship with ZIKV outbreak was unlikely as two cases were GBS controls enrolled 3 months before outbreak. None reported symptoms of ZIKV infection. In addition, compared to last 10 years the national number of GBS hospitalizations did not increase during and immediately after outbreak. We conclude the 2016 Singapore ZIKV outbreak did not cause a change in GBS epidemiology.
The increasing trend in the number new cases of influenza every year as reported by WHO is concerning, especially in Malaysia. To date, there is no local research under healthcare sector that implements the time series forecasting methods to predict future disease outbreak in Malaysia, specifically influenza. Addressing the problem could increase awareness of the disease and could help healthcare workers to be more prepared in preventing the widespread of the disease. This paper intends to perform a hybrid ARIMA-SVR approach in forecasting monthly influenza cases in Malaysia. Autoregressive Integrated Moving Average (ARIMA) model (using Box-Jenkins method) and Support Vector Regression (SVR) model were used to capture the linear and nonlinear components in the monthly influenza cases, respectively. It was forecasted that the performance of the hybrid model would improve. The data from World Health Organization (WHO) websites consisting of weekly Influenza Serology A cases in Malaysia from the year 2006 until 2019 have been used for this study. The data were recategorized into monthly data. The findings of the study showed that the monthly influenza cases could be efficiently forecasted using three comparator models as all models outperformed the benchmark model (Naïve model). However, SVR with linear kernel produced the lowest values of RMSE and MAE for the test dataset suggesting the best performance out of the other comparators. This suggested that SVR has the potential to produce more consistent results in forecasting future values when compared with ARIMA and the ARIMA-SVR hybrid model.
A large scale study was conducted to elucidate the true relationship among entomological, epidemiological and environmental factors that contributed to dengue outbreak in Malaysia. Two large areas (Selayang and Bandar Baru Bangi) were selected in this study based on five consecutive years of high dengue cases. Entomological data were collected using ovitraps where the number of larvae was used to reflect Aedes mosquito population size; followed by RT-PCR screening to detect and serotype dengue virus in mosquitoes. Notified cases, date of disease onset, and number and type of the interventions were used as epidemiological endpoint, while rainfall, temperature, relative humidity and air pollution index (API) were indicators for environmental data. The field study was conducted during 81 weeks of data collection. Correlation and Autoregressive Distributed Lag Model were used to determine the relationship. The study showed that, notified cases were indirectly related with the environmental data, but shifted one week, i.e. last 3 weeks positive PCR; last 4 weeks rainfall; last 3 weeks maximum relative humidity; last 3 weeks minimum and maximum temperature; and last 4 weeks air pollution index (API), respectively. Notified cases were also related with next week intervention, while conventional intervention only happened 4 weeks after larvae were found, indicating ample time for dengue transmission. Based on a significant relationship among the three factors (epidemiological, entomological and environmental), estimated Autoregressive Distributed Lag (ADL) model for both locations produced high accuracy 84.9% for Selayang and 84.1% for Bandar Baru Bangi in predicting the actual notified cases. Hence, such model can be used in forestalling dengue outbreak and acts as an early warning system. The existence of relationships among the entomological, epidemiological and environmental factors can be used to build an early warning system for the prediction of dengue outbreak so that preventive interventions can be taken early to avert the outbreaks.