\ud Detection and Monitoring of Insecticide Resistance in Malaria Vectors in Tanzania Mainland\ud

\ud Vector control is a major component of the global strategy for malaria control which aims to prevent parasite transmission mainly through interventions targeting adult Anopheline vectors. Insecticide treated nets (ITNs) and indoor residual spraying (IRS) are the cornerstone of malaria vector control programmes. These major interventions in most cases use pyrethroid insecticides which are also used for agricultural purposes. With widespread development of resistance to pyrethroid insecticides in malaria vectors raises concern over the sustainability of insecticide-based interventions for malaria control. Therefore, close monitoring of performance of the insecticides against malaria vectors is essential for early detection and\ud management of resistance. To measure pyrethroid susceptibility in populations of malaria vectors in Tanzania and to test the efficacy of LLINs/ITNs and insecticide residues on sprayed wall substrates in the IRS operation areas. In 2011 the National Institute for Medical Research (NIMR) in collaboration with National Malaria Control Programme (NMCP) conducted large scale surveillance to determine the countrywide susceptibility levels of malaria vectors to insecticides used for both public health and agricultural purposes. Anopheles gambiae Giles s.l. were collected during national surveys and samples of LLINs/ITNs in the 14 sentinel sites and houses from the IRS areas were randomly selected for bioassays to test the efficacy and insecticide residual effects on sprayed wall substrates respectively. Wild adult mosquitoes for susceptibility testing were collected by resting catches indoors. Net traps (outdoors and indoors) were set up to enhance catches. WHO Susceptibility kits were used to test for resistance status using test papers: Lambdacyhalothrin 0.05%, Deltamethrin 0.05%, Permethrin 0.75%, DDT 4%, Propoxur 0.1% and Fenitrothion 1%. The quality of the test paper was checked against a laboratory susceptible An. gambiae Kisumu strain. Knockdown effect and mortality were measured in standard WHO susceptibility tests and cone bio-efficacy tests. Whereas, con bioassays on treated walls and ITNs were conducted using the laboratory susceptible An. gambiae Kisumu strain. The results from the surveillance recorded continued susceptibility of malaria vectors to commonly used insecticides. However, there were some isolated cases of resistance and/or reduced susceptibility to pyrethroid insecticides which may not compromise the current vector control interventions in the country. Anopheles gambiae s.l. showed resistance (15-28%) to each of the pyrethroids and to DDT but not to Organophosphates (Propoxur 0.1%), and Carbamates (Fenitrothion 1%). The information obtained from this surveillance is expected to be used to guide the National Malaria Control Programme on the rational selection of insecticides for malaria vector control and for the national mitigation plans for management and containment of malaria vector resistance in the country. The current observation warrants more vigilant monitoring of the susceptibility of malaria mosquitoes to commonly used insecticides in areas found with resistance and/or reduced levels of susceptibility of malaria vectors to insecticides, particularly in areas with heavy agricultural and/or public health use of insecticides where resistance is likely to develop. The current survey covered malaria vectors only and not the non malaria vectors (nuisance) mosquitoes such as Culex. Similar monitoring of insecticide susceptibility of this non malaria vectors may be needed to ensure public motivation for sustained use of ITNs/LLINs in the country. The surveillance leading to these results received funding from PMI/USAID through RTI International with Sub Agreement Number 33300212555.\u

Design and simulation of a multi-function MEMS sensor for health and usage monitoring.

Health and usage monitoring as a technique for online test, diagnosis or prognosis of structures and systems has evolved as a key technology for future critical systems. The technology, often referred to as HUMS is usually based around sensors that must be more reliable than the system or structure they are monitoring. This paper proposes a fault tolerant sensor architecture and demonstrates the feasibility of realising this architecture through the design of a dual mode humidity/pressure MEMS sensor with an integrated temperature function. The sensor has a simple structure, good linearity and sensitivity, and the potential for implementation of built-in-self-test features. We also propose a re-configurable sensor network based on the multi-functional sensor concept that supports both normal operational and fail safe modes. The architecture has the potential to significantly increase system reliability and supports a reduction in the number of sensors required in future HUMS devices. The technique has potential in a wide range of applications, especially within wireless sensor networks

Degradation modeling applied to residual lifetime prediction using functional data analysis

Sensor-based degradation signals measure the accumulation of damage of an engineering system using sensor technology. Degradation signals can be used to estimate, for example, the distribution of the remaining life of partially degraded systems and/or their components. In this paper we present a nonparametric degradation modeling framework for making inference on the evolution of degradation signals that are observed sparsely or over short intervals of times. Furthermore, an empirical Bayes approach is used to update the stochastic parameters of the degradation model in real-time using training degradation signals for online monitoring of components operating in the field. The primary application of this Bayesian framework is updating the residual lifetime up to a degradation threshold of partially degraded components. We validate our degradation modeling approach using a real-world crack growth data set as well as a case study of simulated degradation signals.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS448 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Estimating space-time mean concentrations of nutrients in surface waters of variable depth

A monitoring scheme has been designed to test whether the space-time mean concentration total Nitrogen (N-total) in the surface water in the Northern Frisian Woodlands (NFW, The Netherlands) complies with standards of the European Water Framework directive. Since in statistical testing for compliance monitoring valid estimators for the mean and its variance are important, a design-based method is preferred above a model-based method. In the NFW-area the surface water depth varies in both space and time and can periodically equal zero, due to variation in precipitation and evapotranspiration. To account for this, space-time mean concentrations are estimated by the ratio of the estimated total mass of nutrient and the estimated total volume of water. The method is applied in the period from 1 April to 30 September 2008 to four hydrologically different subareas. Besides, the aim was to use the information on the spatial and temporal variance of N-total concentrations to optimize the numbers of sampling rounds and sampling locations per sampling round in future monitoring campaigns, given budgetary constraints. A bootstrap procedure was applied to account for uncertainty about the temporal and spatial variances in estimating the optimal number of sampling rounds and sampling locations. For two subareas the accuracy of the estimated space-time means can be improved by sampling more frequently at less locations (compared to the design applied in 2008), whereas for one subarea sampling less frequently at more locations increases the precision. For one subarea the sample data were rather inconclusive about the optimal sample sizes

Entomological Surveillance of Behavioural Resilience and Resistance in Residual Malaria Vector Populations.

The most potent malaria vectors rely heavily upon human blood so they are vulnerable to attack with insecticide-treated nets (ITNs) and indoor residual spraying (IRS) within houses. Mosquito taxa that can avoid feeding or resting indoors, or by obtaining blood from animals, mediate a growing proportion of the dwindling transmission that persists as ITNs and IRS are scaled up. Increasing frequency of behavioural evasion traits within persisting residual vector systems usually reflect the successful suppression of the most potent and vulnerable vector taxa by IRS or ITNs, rather than their failure. Many of the commonly observed changes in mosquito behavioural patterns following intervention scale-up may well be explained by modified taxonomic composition and expression of phenotypically plastic behavioural preferences, rather than altered innate preferences of individuals or populations. Detailed review of the contemporary evidence base does not yet provide any clear-cut example of true behavioural resistance and is, therefore, consistent with the hypothesis presented. Caution should be exercised before over-interpreting most existing reports of increased frequency of behavioural traits which enable mosquitoes to evade fatal contact with insecticides: this may simply be the result of suppressing the most behaviourally vulnerable of the vector taxa that constituted the original transmission system. Mosquito taxa which have always exhibited such evasive traits may be more accurately described as behaviourally resilient, rather than resistant. Ongoing national or regional entomological monitoring surveys of physiological susceptibility to insecticides should be supplemented with biologically and epidemiologically meaningfully estimates of malaria vector population dynamics and the behavioural phenotypes that determine intervention impact, in order to design, select, evaluate and optimize the implementation of vector control measures

An accurate method to correct atmospheric phase delay for InSAR with the ERA5 global atmospheric model

Differential SAR Interferometry (DInSAR) has proven its unprecedented ability and merits of monitoring ground deformation on a large scale with centimeter to millimeter accuracy. However, atmospheric artifacts due to spatial and temporal variations of the atmospheric state often affect the reliability and accuracy of its results. The commonly-known Atmospheric Phase Screen (APS) appears in the interferograms as ghost fringes not related to either topography or deformation. Atmospheric artifact mitigation remains one of the biggest challenges to be addressed within the DInSAR community. State-of-the-art research works have revealed that atmospheric artifacts can be partially compensated with empirical models, point-wise GPS zenith path delay, and numerical weather prediction models. In this study, we implement an accurate and realistic computing strategy using atmospheric reanalysis ERA5 data to estimate atmospheric artifacts. With this approach, the Line-of-Sight (LOS) path along the satellite trajectory and the monitored points is considered, rather than estimating it from the zenith path delay. Compared with the zenith delay-based method, the key advantage is that it can avoid errors caused by any anisotropic atmospheric phenomena. The accurate method is validated with Sentinel-1 data in three different test sites: Tenerife island (Spain), Almería (Spain), and Crete island (Greece). The effectiveness and performance of the method to remove APS from interferograms is evaluated in the three test sites showing a great improvement with respect to the zenith-based approach.Peer ReviewedPostprint (published version