Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX.

Chloroquine combined with primaquine has been the standard radical curative regimen forPlasmodium vivaxandPlasmodium ovalemalaria for over half a century. In an open-label crossover pharmacokinetic study, 16 healthy volunteers (4 males and 12 females) aged 20 to 47 years were randomized into two groups of three sequential hospital admissions to receive a single oral dose of 30 mg (base) primaquine, 600 mg (base) chloroquine, and the two drugs together. The coadministration of the two drugs did not affect chloroquine or desethylchloroquine pharmacokinetics but increased plasma primaquine concentrations significantly (P≤ 0.005); the geometric mean (90% confidence interval [CI]) increases were 63% (47 to 81%) in maximum concentration and 24% (13 to 35%) in total exposure. There were also corresponding increases in plasma carboxyprimaquine concentrations (P≤ 0.020). There were no significant electrocardiographic changes following primaquine administration, but there was slight corrected QT (QTc) (Fridericia) interval lengthening following chloroquine administration (median [range] = 6.32 [−1.45 to 12.3] ms;P< 0.001), which was not affected by the addition of primaquine (5.58 [1.74 to 11.4] ms;P= 0.642). This pharmacokinetic interaction may explain previous observations of synergy in preventingP. vivaxrelapse. This trial was registered at ClinicalTrials.gov under reference number NCT01218932.

Background: Plasmodium vivax has a dormant hepatic stage, called the hypnozoite, which can cause relapse months after the initial attack. For 50 years, primaquine has been used as a hypnozoitocide to radically cure P. vivax infection, but major concerns remain regarding the side-effects of the drug and adherence to the 14-day regimen. This study examined the effectiveness of using the directly-observed therapy (DOT) method for the radical treatment of P. vivax malaria infection, to prevent reappearance of the parasite within the 90-day follow-up period. Other potential risk factors for the reappearance of P. vivax were also explored. Methods: A randomized trial was conducted from May 2007 to January 2009 in a low malaria transmission area along the Thai-Myanmar border. Patients aged ≥ 3 years diagnosed with P. vivax by microscopy, were recruited. All patients were treated with the national standard regimen of chloroquine for three days followed by primaquine for 14 days. Patients were randomized to receive DOT or self-administered therapy (SAT). All patients were followed for three months to check for any reappearance of P. vivax. Results: Of the 216 patients enrolled, 109 were randomized to DOT and 107 to SAT. All patients recovered without serious adverse effects. The vivax reappearance rate was significantly lower in the DOT group than the SAT group (3.4/10,000 person-days vs. 13.5/10,000 person-days, p = 0.021). Factors related to the reappearance of vivax malaria included inadequate total primaquine dosage received (< 2.75 mg/kg), duration of fever ≤ 2 days before initiation of treatment, parasite count on admission ≥ 10,000/µl, multiple P. vivax-genotype infection, and presence of P. falciparum infection during the follow-up period. Conclusions: Adherence to the 14-day primaquine regimen is important for the radical cure of P. vivax malaria infection. Implementation of DOT reduces the reappearance rate of the parasite, and may subsequently decrease P. vivax transmission in the area.

Village malaria workers (VMWs) and mobile malaria workers (MMWs) are a critical component of Cambodia’s national strategy to eliminate Plasmodium falciparum malaria by 2025. Since 2004, VMWs have been providing malaria diagnosis through the use of rapid diagnostic tests and free-of-charge artemisinin-based combination therapy in villages more than 5 km away from the closest health facility. They have also played a key role in the delivery of behaviour change communication interventions to this target population. This study aimed to assess the job performance of VMWs/MMWs, and identify challenges they face, which may impede elimination efforts. A mixed-methods assessment was conducted in five provinces of western Cambodia. One hundred and eighty five VMW/MMW participants were surveyed using a structured questionnaire. Qualitative data was gathered through a total of 60 focus group discussions and 65 in-depth interviews. Data triangulation of the qualitative and quantitative data was used during analysis. Overall, VMWs/MMWs met or exceeded the expected performance levels (80 %). Nevertheless, some performance gaps were identified. Misconceptions regarding malaria transmission and prevention were found among workers. The recommended approach for malaria treatment, directly-observed treatment (DOT), had low implementation rates. Stock-outs, difficulties in reaching out to migrant and mobile populations, insufficient means of transportation and dwindling worker satisfaction also affected job performance. VMW/MMW job performance must be increased from 80 to 100 % in order to achieve elimination. In order to do this, it is recommended for the national malaria programme to eliminate worker malaria knowledge gaps. Barriers to DOT implementation and health system failures also need to be addressed. The VMW programme should be expanded on several fronts in order to tackle remaining performance gaps. Findings from this evaluation are useful to inform the planning of future activities of the programme and to improve the effectiveness of interventions in a context where artemisinin drug resistance is a significant public health issue.

In low malaria transmission areas, many people acquire multiple malaria infections within a single season. This study aimed to describe the pattern and epidemiological profile of malaria recurrence in a hypoendemic area of western Thailand and identify factors associated with having multiple malaria episodes. An open cohort of 7000 residents in seven clusters along the Thai-Myanmar border was followed during a 6.5-year period (2011–mid 2017). Symptomatic and asymptomatic malaria infections were detected by passive case detection (PCD), weekly household visit, and mass blood surveys every 4–6 months. Malaria recurrence was defined as subsequent parasitaemic episodes occurred later than 7 days after receiving anti-malarial treatment. This study focused on analysis of recurrent episodes that occurred within 1 year after treatment. Numbers of malaria cases with single and multiple episodes were compared between clusters. Kaplan–Meier curve was performed to determine the intervals of recurrent episodes by Plasmodium species and age groups. The ordinal logistic model was used to determine factors associated with multiple malaria episodes, and to compare with single episodes, and those with no malaria infection. The cumulative incidence of malaria in the study area was 5.2% over the 6.5 years. Overall, 410 malaria patients were detected. Of these patients, 20% and 16% had multiple malaria episodes during the entire period and within 1 year after initial treatment, respectively. About 80% of repeated malaria episodes were caused by the same Plasmodium species as the primary infections. The median interval and interquartile range (IQR) between the first and second episode was 88 (43–175) days for all parasites, 56 (35–133) days for two Plasmodium falciparum episodes, and 90 (59–204) days for two Plasmodium vivax episodes. The interval between the episodes was increased with age. Factors significantly associated with multiple episodes of malaria infection included male sex, young age, Karen ethnicity, forest-related occupation, and having other malaria infected persons in the same house in the same period. People who have multiple malaria episodes may play an important role in maintaining malaria transmission in the area. Understanding epidemiological profiles of this group is important for planning strategies to achieve the elimination goal.

Differentiating dengue patients from other acute febrile illness patients is a great challenge among physicians. Several dengue diagnosis methods are recommended by WHO. The application of specific laboratory tests is still limited due to high cost, lack of equipment, and uncertain validity. Therefore, clinical diagnosis remains a common practice especially in resource limited settings. Bayesian networks have been shown to be a useful tool for diagnostic decision support. This study aimed to construct Bayesian network models using basic demographic, clinical, and laboratory profiles of acute febrile illness patients to diagnose dengue. Data of 397 acute undifferentiated febrile illness patients who visited the fever clinic of the Bangkok Hospital for Tropical Diseases, Thailand, were used for model construction and validation. The two best final models were selected: one with and one without NS1 rapid test result. The diagnostic accuracy of the models was compared with that of physicians on the same set of patients. The Bayesian network models provided good diagnostic accuracy of dengue infection, with ROC AUC of 0.80 and 0.75 for models with and without NS1 rapid test result, respectively. The models had approximately 80% specificity and 70% sensitivity, similar to the diagnostic accuracy of the hospital’s fellows in infectious disease. Including information on NS1 rapid test improved the specificity, but reduced the sensitivity, both in model and physician diagnoses. The Bayesian network model developed in this study could be useful to assist physicians in diagnosing dengue, particularly in regions where experienced physicians and laboratory confirmation tests are limited. In many parts of the world, dengue diagnosis still relies on clinical manifestation and basic laboratory tests. However, clinical manifestation of dengue patients is usually unspecific especially during the early stage, which makes accurate dengue diagnosis a challenge for physicians. Recently, the World Health Organization has recommended the use of the NS1 antigen rapid test to assist in dengue diagnosis. Unfortunately, the rapid test is still only in limited use due to its cost and relatively low sensitivity. In this study we constructed Bayesian Network (BN) models from available data and used them to predict the probability of dengue infection. Our BN models provided good performance in making dengue diagnosis, comparable with physician’s diagnosis. Information on NS1 rapid test could improve the diagnostic performance by improving specificity of dengue diagnosis. This study suggested that BN models can be useful to assist physicians in dengue diagnosis, particularly in areas where experienced physicians and laboratory confirmation tests are limited.