Despite great achievements by insecticide-treated nets (ITNs) and indoor residual spraying (IRS) in reducing malaria transmission, it is unlikely these tools will be sufficient to eliminate malaria transmission on their own in many settings today. Fortunately, field experiments indicate that there are many promising vector control interventions that can be used to complement ITNs and/or IRS by targeting a wide range of biological and environmental mosquito resources. The majority of these experiments were performed to test a single vector control intervention in isolation; however, there is growing evidence and consensus that effective vector control with the goal of malaria elimination will require a combination of interventions.; We have developed a model of mosquito population dynamic to describe the mosquito life and feeding cycles and to optimize the impact of vector control intervention combinations at suppressing mosquito populations. The model simulations were performed for the main three malaria vectors in sub-Saharan Africa, Anopheles gambiae s.s, An. arabiensis and An. funestus. We considered areas having low, moderate and high malaria transmission, corresponding to entomological inoculation rates of 10, 50 and 100 infective bites per person per year, respectively. In all settings, we considered baseline ITN coverage of 50% or 80% in addition to a range of other vector control tools to interrupt malaria transmission. The model was used to sweep through parameters space to select the best optimal intervention packages. Sample model simulations indicate that, starting with ITNs at a coverage of 50% (An. gambiae s.s. and An. funestus) or 80% (An. arabiensis) and adding interventions that do not require human participation (e.g. larviciding at 80% coverage, endectocide treated cattle at 50% coverage and attractive toxic sugar baits at 50% coverage) may be sufficient to suppress all the three species to an extent required to achieve local malaria elimination.; The Vector Control Optimization Model (VCOM) is a computational tool to predict the impact of combined vector control interventions at the mosquito population level in a range of eco-epidemiological settings. The model predicts specific combinations of vector control tools to achieve local malaria elimination in a range of eco-epidemiological settings and can assist researchers and program decision-makers on the design of experimental or operational research to test vector control interventions. A corresponding graphical user interface is available for national malaria control programs and other end users.
from #AlexandrosSfakianakis via Alexandros G.Sfakianakis on Inoreader http://ift.tt/2AENMqB
via IFTTT
Εγγραφή σε:
Σχόλια ανάρτησης (Atom)
Δημοφιλείς αναρτήσεις
-
Abstract Recent updating of the World Health Organization (WHO) classification of central nervous system (CNS) tumors in 2016 demonstrates...
-
In our previous work, the dichloromethane-methanol (1:1 v/v) extract, fractions and isolated compounds from Polyscias fulva stem bark showed...
-
Background Agricultural work can expose workers to increased risk of heat strain and volume depletion due to repeated exposures to high ambi...
-
Cincinnati.com No fooling; go get your head (and neck) examined for free Cincinnati.com Thursday, get your head examined. UC Health ...
-
Nursing students' perceptions of a video-based serious game's educational value: A pilot study. Nurse Educ Today. 2017 Dec 28;...
-
Anaphora is a rhetorical term for the repetition of a word or phrase at the beginning of successive clauses or verses. from #AlexandrosSfa...
-
Abstract We introduce a novel diagnostic Visual Voiding Device (VVD), which has the ability to visually document urinary voiding events an...
-
Method combines radiomics with three - compartment breast image analysis of dual - energy mammography (Source: The Doctors Lounge - Oncology...
-
Cone beam computerized tomography (CBCT) has been widely used in dental implanting. However, the local hospitals usually don’t have access t...
Δεν υπάρχουν σχόλια:
Δημοσίευση σχολίου