Dataset Information

Empirical optimization of risk thresholds for dengue: an approach towards entomological management of Aedes mosquitoes based on larval indices in the Kandy District of Sri Lanka.

ABSTRACT:

Background

Larval indices such as Premise Index (PI), Breteau Index (BI) and Container Index (CI) are widely used to interpret the density of dengue vectors in surveillance programmes. These indices may be useful for forecasting disease outbreaks in an area. However, use of the values of these indices as alarm signals is rarely considered in control programmes. Therefore, the current study aims to propose threshold values for vector indices based on an empirical modeling approach for the Kandy District of Sri Lanka.

Methods

Monthly vector indices, viz PI, BI and CI, for Aedes aegypti and Aedes albopictus, of four selected dengue high risk Medical Officer of Health (MOH) areas in the Kandy District from January 2010 to August 2017, were used in the study. Gumbel frequency analysis was used to calculate the exceedance probability of quantitative values for each individual larval index within the relevant MOH area, individually and to set up the threshold values for the entomological management of dengue vectors.

Results

Among the study MOH areas, Akurana indicated a relatively high density of both Ae. aegypti and Ae. albopictus, while Gangawata Korale MOH area had the lowest. Based on Ae. aegypti, threshold values were defined for Kandy as low risk (BI_agp > 1.77), risk (BI_agp > 3.23), moderate risk (BI_agp > 4.47) and high risk (BI_agp > 6.23). In addition, PI > 6.75 was defined as low risk, while PI > 9.43 and PI>12.82 were defined as moderate and high risk, respectively as an average.

Conclusions

Threshold values recommended for Ae. aegypti (primary vector for dengue) along with cut-off values for PI (for Ae. aegypti and Ae. albopictus), could be suggested as indicators for decision making in vector control efforts. This may also facilitate the rational use of financial allocations, technical and human resources for vector control approaches in Sri Lanka in a fruitful manner.

SUBMITTER: Udayanga L

PROVIDER: S-EPMC6022305 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Publications

Empirical optimization of risk thresholds for dengue: an approach towards entomological management of Aedes mosquitoes based on larval indices in the Kandy District of Sri Lanka.

Udayanga Lahiru L Gunathilaka Nayana N Iqbal Mohamed Cassim Mohamed MCM Najim Mohamed Mujithaba Mohamed MMM Pahalagedara Kusumawathie K Abeyewickreme Wimaladharma W

Parasites & vectors 20180628 1

<h4>Background</h4>Larval indices such as Premise Index (PI), Breteau Index (BI) and Container Index (CI) are widely used to interpret the density of dengue vectors in surveillance programmes. These indices may be useful for forecasting disease outbreaks in an area. However, use of the values of these indices as alarm signals is rarely considered in control programmes. Therefore, the current study aims to propose threshold values for vector indices based on an empirical modeling approach for the ...[more]

PMID: 29954443

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Project description:BackgroundEarly detection of dengue epidemics is a vital aspect in control programmes. Predictions based on larval indices of disease vectors are widely used in dengue control, with defined threshold values. However, there is no set threshold in Sri Lanka at the national or regional levels for Aedes larval indices. Therefore, the current study aimed at developing threshold values for vector indices in two dengue high-risk districts in Sri Lanka.MethodsMonthly vector indices (House Index [HI], Container Index [CI], Breteau Index for Aedes aegypti [BIagp], and Ae. albopictus [BIalb]), of ten selected dengue high-risk Medical Officer of Health (MOH) areas located in Colombo and Kandy districts, were collected from January 2010 to June 2019, along with monthly reported dengue cases. Receiver Operating Characteristic (ROC) curve analysis in SPSS (version 23) was used to assess the discriminative power of the larval indices in identifying dengue epidemics and to develop thresholds for the dengue epidemic management.ResultsOnly HI and BIagp denoted significant associations with dengue epidemics at lag periods of one and two months. Based on Ae. aegypti, average threshold values were defined for Colombo as Low Risk (2.4 ≤ BIagp < 3.8), Moderate Risk (3.8 ≤ BIagp < 5), High Risk (BIagp ≥ 5), along with BIagp 2.9 ≤ BIagp < 4.2 (Low Risk), 4.2 ≤ BIagp < 5.3 (Moderate Risk), and BIagp ≥ 5.3 (High Risk) for Kandy. Further, 5.5 ≤ HI < 8.9, 8.9 ≤ HI < 11.9, and HI ≥ 11.9 were defined as Low Risk, Moderate Risk, and High Risk average thresholds for HI in Colombo, while 6.9 ≤ HI < 9.1 (Low Risk), 8.9 ≥ HI < 11.8 (Moderate Risk), and HI ≥ 11.8 (High Risk) were defined for Kandy.ConclusionsThe defined threshold values for Ae. aegypti and HI could be recommended as indicators for early detection of dengue epidemics and to drive vector management activities, with the objective of managing dengue epidemics with optimal usage of financial, technical, and human resources in Sri Lanka.

Project description:BackgroundLeptospirosis is a bacterial zoonosis. Leptospirosis incidence (LI) in Sri Lanka is high. Infected animals excrete leptospires into the environment via their urine. Survival of leptospires in the environment until they enter into a person and several other factors that influence leptospirosis transmission are dependent upon local weather. Past studies show that rainfall and other weather parameters are correlated with the LI in the Kandy district, Sri Lanka. El Niño Southern Oscillation (ENSO), ENSO Modoki, and the Indian Ocean Dipole (IOD) are teleconnections known to be modulating rainfall in Sri Lanka. There is a severe dearth of published studies on the correlations between indices of these teleconnections and LI.MethodsWe acquired the counts of leptospirosis cases notified and midyear estimated population data of the Kandy district from 2004 to 2019, respectively, from weekly epidemiology reports of the Ministry of Health and Department of Census and Statistics of Sri Lanka. We estimated weekly and monthly LI of Kandy. We obtained weekly and monthly teleconnection indices data for the same period from the National Oceanic and Atmospheric Administration (NOAA) of the USA and Japan Agency for Marine-Earth Science and Technology (JAMSTEC). We performed wavelet time series analysis to determine correlations with lag periods between teleconnection indices and LI time series. Then, we did time-lagged detrended cross-correlation analysis (DCCA) to verify wavelet analysis results and to find the magnitudes of the correlations detected.ResultsWavelet analysis displayed indices of ENSO, IOD, and ENSO Modoki were correlated with the LI of Kandy with 1.9-11.5-month lags. Indices of ENSO showed two correlation patterns with Kandy LI. Time-lagged DCCA results show all indices of the three teleconnections studied were significantly correlated with the LI of Kandy with 2-5-month lag periods.ConclusionsResults of the two analysis methods generally agree indicating that ENSO and IOD modulate LI in Kandy by modulating local rainfall and probably other weather parameters. We recommend further studies about the ENSO Modoki and LI correlation in Sri Lanka. Monitoring for extreme teleconnection events and enhancing preventive measures during lag periods can blunt LI peaks that may follow.

Project description:BackgroundDengue is a major public health problem in Sri Lanka. Aedes vector surveillance and monitoring of larval indices are routine, long-established public health practices in the country. However, the association between Aedes larval indices and dengue incidence is poorly understood. It is crucial to evaluate lagged effects and threshold values of Aedes larval indices to set pragmatic targets for sustainable vector control interventions.MethodsMonthly Aedes larval indices and dengue cases in all 10 Medical Officer of Health (MOH) divisions in Kalutara district were obtained from 2010 to 2019. Using a novel statistical approach, a distributed lag non-linear model and a two-staged hierarchical meta-analysis, we estimated the overall non-linear and delayed effects of the Premise Index (PI), Breteau Index (BI) and Container Index (CI) on dengue incidence in Kalutara district. A set of MOH division-specific variables were evaluated within the same meta-analytical framework to determine their moderator effects on dengue risk. Using generalized additive models, we assessed the utility of Aedes larval indices in predicting dengue incidence.ResultsWe found that all three larval indices were associated with dengue risk at a lag of 1 to 2 months. The relationship between PI and dengue was homogeneous across MOH divisions, whereas that with BI and CI was heterogeneous. The threshold values of BI, PI and CI associated with dengue risk were 2, 15 and 45, respectively. All three indices showed a low to moderate accuracy in predicting dengue risk in Kalutara district.ConclusionsThis study showed the potential of vector surveillance information in Kalutara district in developing a threshold-based, location-specific early warning system with a lead time of 2 months. The estimated thresholds are nonetheless time-bound and may not be universally applicable. Whenever longitudinal vector surveillance data areavailable, the methodological framework we propose here can be used to estimate location-specific Aedes larval index thresholds in any other dengue-endemic setting.

Project description:BackgroundLeishmaniasis is a notifiable disease in Sri Lanka since 2008. Previous studies show a gap in the notification of leishmaniasis. The purpose of the present study was to determine the Knowledge, attitudes and practice of medical officers regarding leishmaniasis.MethodsA cross-sectional study was conducted in the Anuradhapura district which reported the highest case load of leishmaniasis. Medical officers from public and private health care institutes in the area filled a self-administered questionnaire in the presence of the investigators.ResultsOne hundred and eighty-eight (188) medical officers completed the questionnaire. Of them, 95.7% were aware of leishmaniasis as a parasitic infection and 84.7% correctly identified Leishmania donovani as the causative organism in Sri Lanka. From the respondents, 181 (96.8%) knew that the vector of leishmaniasis is sand fly. Cutaneous leishmaniasis was reported as the most prevalent form of leishmaniasis in the country by 176 (94.1%). Nearly half of the respondents (98, 54.1%) were aware of the fact that the Anuradhapura district has the highest disease burden. Many of them had the idea that leishmaniasis is an emerging disease (155, 84.3%,) and early diagnosis is important in controlling the disease (163, 89.1%). Although about three fourth (123, 73.7%,) of the participants mentioned that leishmaniasis should be notified at first clinical suspicion, only 74 (42.5%) were aware that it is a legal requirement. Some medical officers (39, 22%) believed that the current notification system in the country is not effective. Unavailability of notification forms (60, 36.8%) heavy workload (85, 50.3%) and inadequate supportive staff (55, 35.1%) were reported as barriers for timely notification. Even though 105 (58.0%) of medical officers had suspected leishmaniasis during the last 8 years period only 35 (19.4%) had notified.ConclusionsEven though more than 90% of the participants had good theoretical knowledge about leishmaniasis; notification of leishmaniasis is considerably inadequate. This study emphasizes the need for greater efforts to improve the notification of leishmaniasis in Sri Lanka.

Project description:Some arbovirus infections, especially dengue, have increased rapidly over the last few decades in Sri Lanka. Prevalence and distribution of different mosquito species have been limitedly documented, which remains grossly inadequate in providing evidence for potential health risks. In this study, the diversity and species composition of mosquitoes in four selected districts in Sri Lanka (Kurunegala, Gampaha, Kegalle, and Kandy) were investigated. Entomological surveys were conducted from a total of 160 temporary and permanent mosquito breeding habitats identified in the study area from June 2017 to October 2018. Mosquito immature stages were sampled using standard dipping, siphoning, or pipetting methods and identified up to the species level. Percentage relative abundance and habitat characteristics such as species richness, dominance, and Shannon-Weiner diversity were calculated for each surveyed habitat type. Associations between co-occurring species were estimated by Hulbert's coefficient of interspecific association (C8). A total of 4663 mosquito larvae belonging to seven genera and fifteen species of mosquitoes were collected. The relative distribution of mosquito species differed significantly among the four studied districts (X 2 = 143.248; df = 33; P < 0.001). According to Kruskal-Wallis statistics (P < 0.05 at 95% of significance), all diversity indices for immature stages of medically important mosquitoes varied significantly across different breeding sites. Paddy fields had the significantly highest species richness of 4.0 ± 2.82. The coefficients of interspecific association among all the recorded medically important vector mosquitoes were found negative during the present study. The findings of the current study would be useful to identify the entomological potential for disease transmission and facilitate the implementation of appropriate vector control interventions. This would ultimately provide an avenue to improve the personal skills of health staff rather than limiting their knowledge to specified disease vectors, under which the control program is concerned.

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Dataset Information

Empirical optimization of risk thresholds for dengue: an approach towards entomological management of Aedes mosquitoes based on larval indices in the Kandy District of Sri Lanka.

Background

Methods

Results

Conclusions

Publications

Empirical optimization of risk thresholds for dengue: an approach towards entomological management of Aedes mosquitoes based on larval indices in the Kandy District of Sri Lanka.

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