METHODS: An outbreak was declared following the detection of P. malariae in July 2020 and active case detection for malaria was performed by collecting blood samples from residents residing within 2 km radius of Moyog village. Vector prevalence and the efficacy of residual insecticides were determined. Health awareness programmes were implemented to prevent future outbreaks. A survey was conducted among villagers to understand risk behaviour and beliefs concerning malaria.
RESULTS: A total of 5254 blood samples collected from 19 villages. Among them, 19 P. malariae cases were identified, including the index case, which originated from a man who returned from Indonesia. His return from Indonesia and healthcare facilities visit coincided with the movement control order during COVID-19 pandemic when the healthcare facilities stretched its capacity and only serious cases were given priority. Despite the index case being a returnee from a malaria endemic area presenting with mild fever, no malaria test was performed at local healthcare facilities. All cases were symptomatic and uncomplicated except for a pregnant woman with severe malaria. There were no deaths; all patients recovered following treatment with artemether-lumefantrine combination therapy. Anopheles balabacensis and Anopheles barbirostris were detected in ponds, puddles and riverbeds. The survey revealed that fishing and hunting during night, and self-treatment for mild symptoms contributed to the outbreak. Despite the index case being a returnee from a malaria-endemic area presenting with mild fever, no malaria test was performed at local healthcare facilities.
CONCLUSION: The outbreak occurred during a COVID-19 movement control order, which strained healthcare facilities, prioritizing only serious cases. Healthcare workers need to be more aware of the risk of malaria from individuals who return from malaria endemic areas. To achieve malaria elimination and prevention of disease reintroduction, new strategies that include multisectoral agencies and active community participation are essential for a more sustainable malaria control programme.
METHODS: A multi-centre study involving 21 laboratories worldwide generated data on the susceptibility of seven mosquito species (Aedes aegypti, Aedes albopictus, Anopheles gambiae sensu stricto [An. gambiae s.s.], Anopheles funestus, Anopheles stephensi, Anopheles minimus and Anopheles albimanus) to seven public health insecticides in five classes, including pyrethroids (metofluthrin, prallethrin and transfluthrin), neonicotinoids (clothianidin), pyrroles (chlorfenapyr), juvenile hormone mimics (pyriproxyfen) and butenolides (flupyradifurone), in glass bottle assays. The data were analysed using a Bayesian binomial model to determine the concentration-response curves for each insecticide-species combination and to assess the within-bioassay variability in the susceptibility endpoints, namely the concentration that kills 50% and 99% of the test population (LC50 and LC99, respectively) and the concentration that inhibits oviposition of the test population by 50% and 99% (OI50 and OI99), to measure mortality and the sterilizing effect, respectively.
RESULTS: Overall, about 200,000 mosquitoes were tested with the new bottle bioassay, and LC50/LC99 or OI50/OI99 values were determined for all insecticides. Variation was seen between laboratories in estimates for some mosquito species-insecticide combinations, while other test results were consistent. The variation was generally greater with transfluthrin and flupyradifurone than with the other compounds tested, especially against Anopheles species. Overall, the mean within-bioassay variability in mortality and oviposition inhibition were mosquito species-insecticide combinations.
CONCLUSION: Our findings, based on the largest susceptibility dataset ever produced on mosquitoes, showed that the new WHO bottle bioassay is adequate for evaluating mosquito susceptibility to new and promising public health insecticides currently deployed for vector control. The datasets presented in this study have been used recently by the WHO to establish 17 new insecticide discriminating concentrations (DCs) for either Aedes spp. or Anopheles spp. The bottle bioassay and DCs can now be widely used to monitor baseline insecticide susceptibility of wild populations of vectors of malaria and Aedes-borne diseases worldwide.
METHODS: The prevalence of Wolbachia in Culicinae mosquitoes was assessed via PCR with wsp primers. For some of the mosquitoes, in which the wsp primers failed to amplify a product, Wolbachia screening was performed using nested PCR targeting the 16S rRNA gene. Wolbachia sequences were aligned using Geneious 9.1.6 software, analyzed with BLAST, and the most similar sequences were downloaded. Phylogenetic analyses were carried out with MEGA 7.0 software. Graphs were drawn with GraphPad Prism 8.0 software.
RESULTS: A total of 217 adult mosquitoes representing 26 mosquito species were screened. Of these, infections with Wolbachia were detected in 4 and 15 mosquito species using wsp and 16S rRNA primers, respectively. To our knowledge, this is the first time Wolbachia was detected using 16S rRNA gene amplification, in some Anopheles species (some infected with Plasmodium), Culex sinensis, Culex vishnui, Culex pseudovishnui, Mansonia bonneae and Mansonia annulifera. Phylogenetic analysis based on wsp revealed Wolbachia from most of the mosquitoes belonged to Wolbachia Supergroup B. Based on 16S rRNA phylogenetic analysis, the Wolbachia strain from Anopheles mosquitoes were more closely related to Wolbachia infecting Anopheles from Africa than from Myanmar.
CONCLUSIONS: Wolbachia was found infecting Anopheles and other important disease vectors such as Mansonia. Since Wolbachia can affect its host by reducing the life span and provide resistance to pathogen infection, several studies have suggested it as a potential innovative tool for vector/vector-borne disease control. Therefore, it is important to carry out further studies on natural Wolbachia infection in vector mosquitoes' populations as well as their long-term effects in new hosts and pathogen suppression.
METHODS: The protocol of the systematic review was registered at PROSPERO with approval ID CRD42020203046. Three databases (Web of Science, Scopus, and MEDLINE) were searched for studies reporting the prevalence of P. cynomolgi infections in Southeast Asian countries between 1946 and 2020. The pooled prevalence or pooled proportion of P. cynomolgi parasitemia in humans, mosquitoes, and macaques was estimated using a random-effects model. Differences in the clinical characteristics of P. cynomolgi infections were also estimated using a random-effects model and presented as pooled odds ratios (ORs) or mean differences (MDs) with 95% confidence intervals (CIs).
RESULTS: Thirteen studies reporting on the prevalence of naturally acquired P. cynomolgi in humans (3 studies, 21 cases), mosquitoes (3 studies, 28 cases), and macaques (7 studies, 334 cases) were included. The results demonstrated that the pooled proportion of naturally acquired P. cynomolgi in humans was 1% (95% CI, 0.1%, I2, 0%), while the pooled proportion of P. cynomolgi infecting mosquitoes was 18% (95% CI, 10-26%, I2, 32.7%). The pooled prevalence of naturally acquired P. cynomolgi in macaques was 47% (95% CI, 27-67%, I2, 98.3%). Most of the cases of naturally acquired P. cynomolgi in humans were reported in Cambodia (62%) and Malaysia (38%), while cases of P. cynomolgi in macaques were reported in Malaysia (35.4%), Singapore (23.2%), Indonesia (17.3%), Philippines (8.5%), Laos (7.93%), and Cambodia (7.65%). Cases of P. cynomolgi in mosquitoes were reported in Vietnam (76.9%) and Malaysia (23.1%).
CONCLUSIONS: This study demonstrated the occurrence of naturally acquired P. cynomolgi infection in humans, mosquitoes, and macaques. Further studies of P. cynomolgi in asymptomatic human cases in areas where vectors and natural hosts are endemic are extensively needed if human infections with P. cynomolgi do become public health problems.
Methods: In this present study, two protein extractions methods were performed to analyze female Ae. aegyti proteome, via TCA acetone precipitation extraction method and a commercial protein extraction reagent CytoBusterTM. Then, protein identification was performed by LC-ESI-MS/MS and followed by functional protein annotation analysis.
Results: The CytoBusterTM reagent gave the highest protein yield with a mean of 475.90 µg compared to TCA acetone precipitation extraction showed 283.15 µg mean of protein. LC-ESI-MS/MS identified 1,290 and 890 proteins from the CytoBusterTM reagent and TCA acetone precipitation, respectively. When comparing the protein class categories in both methods, there were three additional categories for proteins identified using CytoBusterTM reagent. The proteins were related to scaffold/adaptor protein (PC00226), protein binding activity modulator (PC00095) and intercellular signal molecule (PC00207). In conclusion, the CytoBusterTM protein extraction reagent showed a better performance for the extraction of proteins in term of the protein yield, proteome coverage and extraction speed.