Dataset Information

Spatial-temporal variation and primary ecological drivers of Anopheles sinensis human biting rates in malaria epidemic-prone regions of China.

ABSTRACT:

Background

Robust malaria vector surveillance is essential for optimally selecting and targeting vector control measures. Sixty-two vector surveillance sites were established between 2005 and 2008 by the national malaria surveillance program in China to measure Anopheles sinensis human biting rates. Using these data to determine the primary ecological drivers of malaria vector human biting rates in malaria epidemic-prone regions of China will allow better targeting of vector control resources in space and time as the country aims to eliminate malaria.

Methods

We analyzed data from 62 malaria surveillance sentinel sites from 2005 to 2008. Linear mixed effects models were used to identify the primary ecological drivers for Anopheles sinensis human biting rates as well as to explore the spatial-temporal variation of relevant factors at surveillance sites throughout China.

Results

Minimum semimonthly temperature (? = 2.99; 95% confidence interval (CI) 2.07- 3.92), enhanced vegetation index (? =1.07; 95% CI 0.11-2.03), and paddy index (the percentage of rice paddy field in the total cultivated land area of each site) (? = 0.86; 95% CI 0.17-1.56) were associated with greater An. Sinensis human biting rates, while increasing distance to the nearest river was associated with lower An. Sinensis human biting rates (? = -1.47; 95% CI -2.88, -0.06). The temporal variation (?(s0)(2) = 0.83) in biting rates was much larger than the spatial variation (?(t)(2) = 1.35), with 19.3% of temporal variation attributable to differences in minimum temperature and enhanced vegetation index and 16.9% of spatial variance due to distance to the nearest river and the paddy index.

Discussion

Substantial spatial-temporal variation in An. Sinensis human biting rates exists in malaria epidemic-prone regions of China, with minimum temperature and enhanced vegetation index accounting for the greatest proportion of temporal variation and distance to nearest river and paddy index accounting for the greatest proportion of spatial variation amongst observed ecological drivers.

Conclusions

Targeted vector control measures based on these findings can support the ongoing malaria elimination efforts in China more effectively.

SUBMITTER: Ren Z

PROVIDER: S-EPMC4303435 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatial-temporal variation and primary ecological drivers of Anopheles sinensis human biting rates in malaria epidemic-prone regions of China.

Ren Zhoupeng Z Wang Duoquan D Hwang Jimee J Bennett Adam A Sturrock Hugh J W HJ Ma Aimin A Huang Jixia J Xia Zhigui Z Feng Xinyu X Wang Jinfeng J

PloS one 20150122 1

<h4>Background</h4>Robust malaria vector surveillance is essential for optimally selecting and targeting vector control measures. Sixty-two vector surveillance sites were established between 2005 and 2008 by the national malaria surveillance program in China to measure Anopheles sinensis human biting rates. Using these data to determine the primary ecological drivers of malaria vector human biting rates in malaria epidemic-prone regions of China will allow better targeting of vector control reso ...[more]

PMID: 25611483

Similar Datasets

Project description:BackgroundThe use of insecticide-treated nets for malaria control has been associated with shifts in mosquito vector feeding behaviour including earlier and outdoor biting on humans. The relative contribution of phenotypic plasticity and heritability to these behavioural shifts is unknown. Elucidation of the mechanisms behind these shifts is crucial for anticipating impacts on vector control.MethodsA novel portable semi-field system (PSFS) was used to experimentally measure heritability of biting time in the malaria vector Anopheles arabiensis in Tanzania. Wild An. arabiensis from hourly collections using the human landing catch (HLC) method were grouped into one of 3 categories based on their time of capture: early (18:00-21:00), mid (22:00-04:00), and late (05:00-07:00) biting, and placed in separate holding cages. Mosquitoes were then provided with a blood meal for egg production and formation of first filial generation (F1). The F1 generation of each biting time phenotype category was reared separately, and blood fed at the same time as their mothers were captured host-seeking. The resultant eggs were used to generate the F2 generation for use in heritability assays. Heritability was assessed by releasing F2 An. arabiensis into the PSFS, recording their biting time during a human landing catch and comparing it to that of their F0 grandmothers.ResultsIn PSFS assays, the biting time of F2 offspring (early: 18:00-21:00, mid: 22:00-04:00 or late: 05:00-07:00) was significantly positively associated with that of their wild-caught F0 grandmothers, corresponding to an estimated heritability of 0.110 (95% CI 0.003, 0.208). F2 from early-biting F0 were more likely to bite early than F2 from mid or late-biting F0. Similarly, the probability of biting late was higher in F2 derived from mid and late-biting F0 than from early-biting F0.ConclusionsDespite modest heritability, our results suggest that some of the variation in biting time is attributable to additive genetic variation. Selection can, therefore, act efficiently on mosquito biting times, highlighting the need for control methods that target early and outdoor biting mosquitoes.

Project description:BackgroundHistorically, malaria due to Plasmodium vivax has been epidemic in Henan Province, China, with Anopheles sinensis as the main vector. The most effective measures to prevent malaria transmission are based on vector control through the use of insecticides. However, insecticides exert a strong selective pressure on mosquito populations for insecticide resistance. The aim of this study was to investigate the susceptibility profile and population genetic characteristics of An. sinensis to provide basic data and scientific guidance for the study of resistance mechanisms and the control of An. sinensis in Henan Province.MethodsAdult Anopheles mosquitoes were collected at sites near local farmers' sheepfolds, pigsties and/or cowsheds located in Pingqiao, Xiangfu, Xiangcheng and Tanghe counties/districts of Henan Province during July-September 2021 for insecticide susceptibility testing. Molecular identification of collected mosquitoes as belonging to genus Anopheles was by PCR, and the frequencies of mutations in the knockdown resistance gene (kdr) and acetylcholinesterase-1 gene (ace-1) were detected using gene amplification. The mitochondrial DNA cytochrome oxidase subunit I (COI) gene was amplified in deltamethrin-resistant and deltamethrin-sensitive mosquitoes to analyze the genetic evolutionary relationship.ResultsA total of 1409 Anopheles mosquitoes were identified by molecular identification, of which 1334 (94.68%) were An. sinensis, 28 (1.99%) were An. yatsushiroensis, 43 (3.05%) were An. anthropophagus and four (0.28%) were An. belenrae. The 24-h mortality rates of An. sinensis in Pingqiao, Tanghe, Xiangcheng and Xiangfu counties/districts exposed to deltamethrin were 85.85%, 25.38%, 29.73% and 7.66%, respectively; to beta-cyfluthrin, 36.24%, 70.91%, 34.33% and 3.28%, respectively; to propoxur, 68.39%, 80.60%, 37.62% and 9.29%, respectively; and to malathion, 97.43%, 97.67%, 99.21% and 64.23%, respectively. One mutation, G119S, was detected in the ace-1 gene. The frequencies of the main genotypes were 84.21% of specimens collected in Xiangfu (G/S), 90.63% of speciments collected in Xiangcheng (G/G) and 2.44% of speciments collected in Tanghe (S/S). Significantly higher G119S allele frequencies were observed in both propoxur- and malathion-resistant mosquitoes than in their sensitive counterparts in the Tanghe population (P < 0.05). Three mutations, L1014F (41.38%), L1014C (9.15%) and L1014W (0.12%), were detected in the kdr gene. The genotypes with the highest frequency in the populations of An. sinensis in Xiangfu and Tanghe were the mutant TTT (F/F) and wild-type TTG (L/L), at 67.86% (57/84) and 74.29% (52/70), respectively. In Pingqiao and Xiangfu, higher frequencies of the L1014F allele and lower frequencies of the L1014C allele were observed in mosquitoes resistant for beta-cyfluthrin than in those which were sensitive for this insecticide (P < 0.05). The results of Tajima's D and of Fu and Li's D and F were not significantly negative (P > 0.10), and each haplotype was interlaced and did not form two distinct branches.ConclusionsHigh resistance to pyrethroids and propoxur was observed at four sites, but the resistance to malathion varied according to the location. Anopheles belenrae and the L1014W (TGG) mutation in An. sinensis were first discovered in Henan Province. The deltamethrin-resistant and deltamethrin-sensitive mosquito populations showed no genetic differentiation. The generation of resistance might be the result of the combination of multiple factors.

Project description:BackgroundThe human biting rate (HBR), an important parameter for assessing malaria transmission and evaluating vector control interventions, is commonly estimated by human landing collections (HLC). Although intense efforts have been made to find alternative non-exposure mosquito collection methods, HLC remains the standard for providing reliable and consistent HBRs. The aim of this study was to assess the relationship between human landing and light trap collections (LTC), in an attempt to estimate operationally feasible conversion factors between the two. The study was conducted as part of the operational research component of the Bioko Island Malaria Control Project (BIMCP), Equatorial Guinea.MethodsMalaria mosquitoes were collected indoors and outdoors by HLCs and LTCs in three villages on Bioko Island, Equatorial Guinea during five bimonthly collections in 2009. Indoor light traps were suspended adjacent to occupied long-lasting, insecticide-treated bed nets. Outdoor light traps were placed close to the outer wall under the roof of the collection house. Collected specimens were subjected to DNA extraction and diagnostic PCR to identify species within the Anopheles gambiae complex. Data were analysed by simple regression of log-transformed values and by Bayesian regression analysis.ResultsThere was a poor correlation between the two collection methods. Results varied by location, venue, month, house, but also by the statistical method used. The more robust Bayesian analyses indicated non-linear relationships and relative sampling efficiencies being density dependent for the indoor collections, implying that straight-forward and simple conversion factors could not be calculated for any of the locations. Outdoor LTC:HLC relationships were weak, but could be estimated at 0.10 and 0.07 for each of two locations.ConclusionsLight trap collections in combination with bed nets are not recommended as a reliable method to assess human biting rates on Bioko Island. Different statistical analyses methods give variable and inconsistent results. Substantial variation in collection methods prevents the determination of reliable and operationally feasible conversion factors for both indoor and outdoor data. Until improved mosquito collection methods are developed that can provide reliable and unbiased HBR estimates, HLCs should continue to serve as the reference method for HBR estimation.

Project description:Anopheles calderoni was first recognized in Colombia in 2010 as this species had been misidentified as Anopheles punctimacula due to morphological similarities. An. calderoni is considered a malaria vector in Peru and has been found naturally infected with Plasmodium falciparum in Colombia. However, its biting behaviour, population dynamics and epidemiological importance have not been well described for Colombia.To assess the contribution of An. calderoni to malaria transmission and its human biting behaviour and spatial/temporal distribution in the southwest of Colombia, human landing catches (HLC) and larval collections were carried out in a cross-sectional, entomological study in 22 localities between 2011 and 2012, and a longitudinal study was performed in the Boca de Prieta locality in Olaya Herrera municipality between July 2012 and June 2013. All mosquitoes determined as An. calderoni were tested by ELISA to establish infection with Plasmodium spp.Larvae of An. calderoni were found in four localities in 12 out of 244 breeding sites inspected. An. calderoni adults were collected in 14 out of 22 localities during the cross-sectional study and represented 41.3% (459 of 1,111) of the collected adult specimens. Other species found were Anopheles albimanus (54.7%), Anopheles apicimacula (2.1%), Anopheles neivai (1.7%), and Anopheles argyritarsis (0.2%). In the localities that reported the highest malaria Annual Parasite Index (>10/1,000 inhabitants) during the year of sampling, An. calderoni was the predominant species (>90% of the specimens collected). In the longitudinal study, 1,528 An. calderoni were collected by HLC with highest biting rates in February, May and June 2013, periods of high precipitation. In general, the species showed a preference to bite outdoors (p < 0.001). In Boca de Prieta, two specimens of An. calderoni were ELISA positive for Plasmodium circumsporozoite protein: one for P. falciparum and one for Plasmodium vivax VK-210. This represents an overall sporozoite rate of 0.1% and an annual entomological inoculation rate of 2.84 infective bites/human/year.This study shows that An. calderoni is a primary malaria vector in the southwest of Colombia. Its observed preference for outdoor biting is a major challenge for malaria control.

Dataset Information

Spatial-temporal variation and primary ecological drivers of Anopheles sinensis human biting rates in malaria epidemic-prone regions of China.

Background

Methods

Results

Discussion

Conclusions

Publications

Spatial-temporal variation and primary ecological drivers of Anopheles sinensis human biting rates in malaria epidemic-prone regions of China.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets