5. Insecticide-impregnated screens used under ‘multi-target method’ for haematophagous fly control in cattle: a proof of concept

Stomoxys flies are mechanical vectors of pathogens present in the blood and skin of their animal hosts, especially livestock, but occasionally humans. In livestock, their direct effects are disturbance, skin lesions, reduction of food intake, stress, blood loss, and a global immunosuppressive effect. They also induce the gathering of animals for mutual protection; meanwhile they favor development of pathogens in the hosts and their transmission. Their indirect effect is the mechanical transmission of pathogens. In case of interrupted feeding, Stomoxys can re-start their blood meal on another host. When injecting saliva prior to blood-sucking, they can inoculate some infected blood remaining on their mouthparts. Beside this immediate transmission, it was observed that Stomoxys may keep some blood in their crop, which offers a friendly environment for pathogens that could be regurgitated during the next blood meal; thus a delayed transmission by Stomoxys seems possible. Such a mechanism has a considerable epidemiological impact since it allows inter-herd transmission of pathogens. Equine infectious anemia, African swine fever, West Nile, and Rift Valley viruses are known to be transmitted by Stomoxys, while others are suspected. Rickettsia (Anaplasma, Coxiella), other bacteria and parasites (Trypanosoma spp., Besnoitia spp.) are also transmitted by Stomoxys. Finally, Stomoxys was also found to act as an intermediate host of the helminth Habronema microstoma and may be involved in the transmission of some Onchocerca and Dirofilaria species. Being cosmopolite, Stomoxys calcitrans might have a worldwide and greater impact than previously thought on animal and human pathogen transmission.

Anesthesia, critical care, perioperative, and pain research often involves study designs in which the same outcome variable is repeatedly measured or observed over time on the same patients. Such repeatedly measured data are referred to as longitudinal data, and longitudinal study designs are commonly used to investigate changes in an outcome over time and to compare these changes among treatment groups. From a statistical perspective, longitudinal studies usually increase the precision of estimated treatment effects, thus increasing the power to detect such effects. Commonly used statistical techniques mostly assume independence of the observations or measurements. However, values repeatedly measured in the same individual will usually be more similar to each other than values of different individuals and ignoring the correlation between repeated measurements may lead to biased estimates as well as invalid P values and confidence intervals. Therefore, appropriate analysis of repeated-measures data requires specific statistical techniques. This tutorial reviews 3 classes of commonly used approaches for the analysis of longitudinal data. The first class uses summary statistics to condense the repeatedly measured information to a single number per subject, thus basically eliminating within-subject repeated measurements and allowing for a straightforward comparison of groups using standard statistical hypothesis tests. The second class is historically popular and comprises the repeated-measures analysis of variance type of analyses. However, strong assumptions that are seldom met in practice and low flexibility limit the usefulness of this approach. The third class comprises modern and flexible regression-based techniques that can be generalized to accommodate a wide range of outcome data including continuous, categorical, and count data. Such methods can be further divided into so-called “population-average statistical models” that focus on the specification of the mean response of the outcome estimated by generalized estimating equations, and “subject-specific models” that allow a full specification of the distribution of the outcome by using random effects to capture within-subject correlations. The choice as to which approach to choose partly depends on the aim of the research and the desired interpretation of the estimated effects (population-average versus subject-specific interpretation). This tutorial discusses aspects of the theoretical background for each technique, and with specific examples of studies published in Anesthesia & Analgesia, demonstrates how these techniques are used in practice.