Comparison between anopheline mosquitoes (Diptera: Culicidae) caught using different methods in a malaria endemic area of Papua New Guinea

Abstract

The mosquito sampling efficiency of CDC (Centers for Disease Control) miniature light traps hung adjacent to mosquito nets, was compared with that of both indoor and outdoor human-bait collections in ten villages in the Wosera area of Papua New Guinea. The most frequently collected anopheline in the matched indoor and light trap samples was Anopheles koliensis Owen, followed by A. punctulatus Dönitz, A. karwari (James), A. farauti Laveran (sensu lato), A. longirostris Brug and A. bancroftii Giles. All species were much less frequent in the light traps than in landing catches. The hypothesis that the numbers of mosquitoes in light traps are proportional to human landing catches was examined using regression models that allowed for sampling error in both entomological measurements. Light traps under-sampled A. punctulatus and A. farauti s.l. at high densities. The models indicated that the ratio of light trap to landing catch females of A. koliensis and A. karwari increased with increasing mosquito density. Light trap catches of A. longirostris were proportional to indoor landing rates but when outdoor landing rates were high this species was under-sampled by light traps. Numbers of A. bancroftii in light traps were found to be proportional to those in outdoor landing catches, but were negatively related to those attempting to bite indoors. Circumsporozoite positivity rates for both Plasmodium falciparum Welch and P. vivax (Grassi & Feletti) in A. punctulatus and A. farauti s.l. were significantly higher in light trap collections than in either indoor or outdoor landing catches, suggesting that light traps may selectively sample older mosquitoes of these species.

Comparative Evaluation of Methods Used for Sampling Malaria Vectors in the Kilombero Valley, South Eastern Tanzania

“…We have determined that the HLC is more efficient than both the CDC-LT and the Mbita trap in the study area. Though these findings support previous arguments that the HLC is the most appropriate sampling method for anthropophilic Anopheles mosquitoes [2,12,23,32,33], the computed sampling efficiencies are of substantial epidemiological significance. However, to avoid overestimation or underestimation of malaria transmission, case by case calibration of CDC-LT to HLC [12,13,34] is recommended.…”

“…Alternatives to human landing catches therefore generally rely on traps baited with humans or with whole human odor. These include Centers for Disease Control light traps (CDC-LT) placed beside occupied untreated bednets [11][12][13], odor baited entry traps [14] and Mbita trap [15,16]. In this category also are the odor baited counter flow geometry traps such as the Mosquito Magnet models of the American biophysics corporation [17][18][19].…”

Malaria infections are randomly distributed in diverse holoendemic areas of Papua New Guinea.

“…[17][18][19] Entomologic inoculation rates (defined as the average number of infectious bites/person/night) for these areas are observed to vary (0.15-0.70). 17,[20][21][22] Earlier blood smear surveys reported overall Plasmodium infection prevalence in these areas as 60% and 37.5%. 18,19 In the Wosera, malariometric indices have shown slight irregular changes over time, but, in general, there is no clear-cut seasonal transmission pattern.…”

High Levels of Genetic Diversity of Plasmodium falciparum Populations in Papua New Guinea despite Variable Infection Prevalence

“…22 and multiple clones observed in 40-50% of infections. 2,23 Although traditionally considered holoendemic, 24,25 more recently malaria transmission in the Wosera region of the East Sepik Province has dropped, ranging between 0.15 and 0.7 infective bites/person/night [26][27][28] with an infection prevalence of 19.5-23.9% 29 and multiple infections are observed in 26% of infections, 29 below that observed in many other parts of Madang and East Sepik Province. 15 The study sites in Madang included 12 villages distributed among three catchment areas-Mugil: comprising Matukar, Bunu, Karkum, and Dimer; Malala: comprising Wakorma, Malala, Suraten, Amiten, and Susure; and Utu: comprising three villages around the region around the village of Utu Sub-Health Center.…”