Modelling the Survival of Western Honey Bee Apis mellifera and the African Stingless Bee Meliponula ferruginea Using Semiparametric Marginal Proportional Hazards Mixture Cure Model

Classical survival analysis assumes all subjects will experience the event of interest, but in some cases, a portion of the population may never encounter the event. These survival methods further assume independent survival times, which is not valid for honey bees, which live in nests. The study introduces a semi-parametric marginal proportional hazards mixture cure (PHMC) model with exchangeable correlation structure, using generalized estimating equations for survival data analysis. The model was tested on clustered right-censored bees survival data with a cured fraction, where two bee species were subjected to different entomopathogens to test the effect of the entomopathogens on the survival of the bee species. The Expectation-Solution algorithm is used to estimate the parameters. The study notes a weak positive association between cure statuses (ρ1=0.0007) and survival times for uncured bees (ρ2=0.0890), emphasizing their importance. The odds of being uncured for A. mellifera is higher than the odds for species M. ferruginea. The bee species, A. mellifera are more susceptible to entomopathogens icipe 7, icipe 20, and icipe 69. The Cox-Snell residuals show that the proposed semiparametric PH model generally fits the data well as compared to model that assume independent correlation structure. Thus, the semi parametric marginal proportional hazards mixture cure is parsimonious model for correlated bees survival data.

Mapping Air Quality Using Remote Sensing Technology: A Case Study of Nairobi County

Nairobi County experiences rapid industrialization and urbanization that contributes to the deteriorating state of air quality, posing a potential health risk to its growing population. Currently, in Nairobi County, most air quality monitoring stations use low-cost, inaccurate monitors prone to defects. The study’s objective was to map Nairobi County’s air quality using freely available remotely sensed imagery. The Air Pollution Index (API) formula was used to characterize the air quality from cloud-free Landsat satellite images i.e., Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 OLI from Google Earth Engine. The API values were computed based on vegetation indices namely NDVI, TVI, DVI, and the SWIR1 and NIR bands on the QGIS platform. Qualitative accuracy assessment was done using sample points drawn from residential, industrial, green spaces, and traffic hotspot categories, based on a passive-random sampling technique. In this study, Landsat 5 API imagery for 2010 provided a reliable representation of local conditions but indicated significant pollution in green spaces, with recorded values ranging from -143 to 334. The study found that Landsat 7 API imagery in 2002 showed expected results with the range of values being -55 to 287, while Landsat 8 indicated high pollution levels in Nairobi. The results emphasized the importance of air quality factors in API calibration and the unmatched spatial coverage of satellite observations over ground-based monitoring techniques. The study recommends the recalibration of the API formula for characteristic regions, exploring newer satellite sensors like those onboard Landsat 9 and Sentinel 2, and involving key stakeholders in a discourse to develop a suitable Kenyan air quality index.

High Dimension Multivariate Data Analysis for Small Group Samples of Chemical Volatile Profiles of African Nightshade Species

Quantitative headspace analysis of volatiles emitted by plants or any other living organisms in chemical ecology studies generates large multidimensional data that require extensive mining and refining to extract useful information. More often the number of variables and the quantified volatile compounds exceed the number of observations or samples and hence many traditional statistical analysis methods become inefficient. Here, we employed machine learning algorithm, random forest (RF) in combination with distance-based procedure, similarity percentage (SIMPER) as preprocessing steps to reduce the data dimensionality in the chemical profiles of volatiles from three African nightshade plant species before subjecting the data to non-metric multidimensional scaling (NMDS). In addition, non-parametric methods namely permutational multivariate analysis of variance (PERMANOVA) and analysis of similarities (ANOSIM) were applied to test hypothesis of differences among the African nightshade species based on the volatiles profiles and ascertain the patterns revealed by NMDS plots. Our results revealed that there were significant differences among the African nightshade species when the data’s dimension was reduced using RF variable importance and SIMPER, as also supported by NMDS plots that showed S. scabrum being separated from S. villosum and S. sarrachoides based on the reduced data variables. The novelty of our work is on the merits of using data reduction techniques to successfully reveal differences in groups which could have otherwise not been the case if the analysis were performed on the entire original data matrix characterized by small samples. The R code used in the analysis has been shared herein for interested researchers to customise it for their own data of similar nature.

Comparison of Semi-Parametric Shared Frailty Models for Bees’Survival

Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may not accurately capture the interdependence among individuals within a colony. Frailty models, accounting for shared risks within groups, offer a promising alternative. This study evaluates the performance of semi-parametric shared frailty models (gamma, inverse normal, and positive stable-in comparison to the traditional Cox model using bees’ survival data). We examined the effect of misspecification of the frailty distribution on regression and heterogeneity parameters using simulation and concluded that the heterogeneity parameter was more sensitive to misspecification of the frailty distribution and choice of initial parameters (cluster size and true heterogeneity parameter) compared to the regression parameter. From the data, parameter estimates for covariates were close for the four models but slightly higher for the Cox model. The shared gamma frailty model provided a better fit to the data in comparison with the other models. Therefore, when focusing on regression parameters, the gamma frailty model is recommended. This research underscores the importance of tailored survival methodologies for accurately analyzing time-to-event data in social organisms.

Molecular Investigation of Genetic Signatures of Selection in <i>Plasmodium falciparum</i>Actin-Binding Protein Coronin, Cysteine Desulfurase, and Plasmepsin 2 Gene in Mbita Field Isolates, Western Kenya

Background: Plasmodium falciparum (Pf) resistance to antimalarial drugs is a major impediment to malaria control. The Pf.Kelch 13 (PfK13) gene has been largely reported to be associated with artemisinin resistance. However, recent studies have shown artemisinin resistance without Kech13 mutations suggesting the implication of others genes in artemisinin resistance. In this current study, we focused on mutations in Pf.actin-binding protein coronin, Pf.cysteine desulfurase and Pf.plasmepsin 2 gene, three putative candidates recently were reported to be involved in artemisinin, lumefantrine and piperaquine resistance respectively. Method: Archived blood samples previously collected from asymptomatic school children from December 2016 to October 2018 were used in this study. Genomic DNA was extracted using ISOLATE II Genomic DNA kit. After PCR amplification, amplicons were purified and sequenced by capillary sequencing. Reads were analyzed for the identification of point mutations previously reported to be involved in drug selection. Results: Mutations R100K, and G50E involved in reduced artemisinin susceptibility were detected in Pfcoronin. From 2016/17 to 2018 the allele 100k increased frequency (11.2%);while 50E was only observed in 2018 time point reaching 11.1%. Lumefantrine selection marker K65, in codon (K65Q) was observed at 14.2% in Pfcysteine desulfurase, and the mutant’ allele 65Q gradually increased frequency from 28.5% in 2016/17 to 57.1% in 2018. Pf.plasmepsin 2 was the less polymorphic gene. Several other polymorphism codons and single nucleotide variants were detected. Conclusion: The findings indicate the presence of mutations associated with reduced artemisinin susceptibility and lumefantrine selection marker. Therefore, the results call for continuous monitoring of molecular makers in Mbita parasites.

Management of <i>Helicoverpa armigera</i>(Lepidoptera: Noctuidae) by Nutritional Indices and Botanical Extracts of <i>Millettia ferruginea</i>and <i>Azadirachta indica</i>

The development of hosts that are resistant and evaluation of botanical extracts to H. armigera Hübner (Lepidoptera: Noctuidae) is crucial for sustainable management, yet very limited in Ethiopia. Therefore, this study was done to identify alternative methods to insecticide control through host consumption study and botanical extracts. The performance of third-fifth larval stages of H. armigera on three host plant varieties including chickpea, tomato and faba bean and botanical extracts against the third larval instars and oviposition deterrence was studied under laboratory condition (22°C ± 2°C, 55% ± 5% RH, 12:12 L: D photoperiod). Significant differences were found in the efficiency of conversion of ingested food (ECI%) (F = 80.06;df = 6, 2;p H. armigera reared on the three host plant varieties of the whole larval instars. The minimum relative consumption rate (RCR) (11.271 ± 0.328) and maximum approximate digestibility (AD) (177.9 ± 1.928) values of the whole larval instars were on Dagaga and Koshari, respectively. The values of relative growth rate (RGR), ECI% and ECD% of the whole larval instars were highest on chickpea varieties and lowest on tomato Koshari. Among chickpea varieties, Habru was relatively resistant to larval instars of H. armigera. Botanical extracts at 50% neem oil (NO), 5% birbira seed extract (BSE) and 5% neem seed extract (NSE) (18.4%) resulted superior in larval mortality however, statistically not different. At both 5% and 2.5% concentration level of botanical extracts the minimum larval mortality was recorded from neem leaf extract (NLE). Maximum numbers of eggs were laid on control treatments and the minimum eggs were on 5% BSE. The deterrent effect of 50% neem oil was stronger (ODI = 17.66%) than that of 5% BSE (ODI = 14%) which is statistically similar value with 5% NSE (ODI = 13%). In conclusion, the result indicated that use of Habru chickpea variety with 50% NO was very effective in controlling both the larvae and deterring the adults of H. armigera from egg lying. These measures could be important in the wider managements of H. armigera by integrating host resistance and botanical extracts.

Efficacy of Metarhizium anisopliae in controlling the two-spotted spider mite Tetranychus urticae on common bean in screenhouse and field experiments

The efficacy of aqueous and emulsifiable formulations of the fungus Metarhizium anisopliae isolate ICIPE78 was evaluated on the population density of Tetranychus urticae infesting common bean plants under screenhouse and field conditions. Synthetic acaricide abamectin was included as a check. Bean plants were artificially infested with T. urticae and allowed to multiply. Three treatments were applied in the screenhouse and 1 treatment in field trials. Mite density was recorded 2 d before spraying and weekly postspraying. The number of pods per plant, number of seeds per pod, and the dry weight of seeds per plant were recorded only in the screenhouse trials. In both screenhouse and field trials, fungal formulations applied at the concentration of 108 conidia/mL and the aearicide reduced the population density of mites as compared to the controls. There were signif- icant differences in T. urticae population densities between the treatments at the various post-spraying sampling dates. In the screenhouse, the mite densities were near zero from 3-week postspraying in the treated leaves. At 4-week postspraying, there were no more leaves in the untreated control （T1） and in the control water ＋ Silwet-L77 （T2）. Fungal formulations were as effective as abamectin in reducing mite densities in both screenhouse and field experiments. There were significant differences in the production parameters during the 2 screenhouse trials, with fungal and abamectin treatments generally having the highest yield. Results of this study underline the potential of the M. anisopliae isolate ICIPE78 as an alternative to acaricides for T. urticae management.

水稻种植区疟疾媒介环境生产力与地面植被覆盖的关系(英文)

本文选择了肯尼亚Mwea水稻种植区中Kangichiri、Kiuria和Rurumi3个村庄-农田交错地区为观察区,分析并比较了2种卫星数据对水稻种植区疟疾媒介分布的指示情况。首先运用2005年7月获取的Quickbird(分辨率0.6m)和Ikonos(分辨率4m)卫星数据在ErdasImagineV8.7中生成观察区的地面植被覆盖图;并于2005年的7月至2006的7月观察相应地区地面蚊虫消长情况。通过对观察区的卫星数据的最大似然法监测分类,并于分类后对每一田块与灌溉渠道都用Arc Info9.1进行栅格矢量化处理(每一栅格设置唯一的标识)。所有调查的蚊虫滋生点,依照水稻的生育期的不同分为6层进行分析。然后将经差分GPS定位的每一处水稻田及按蚊产卵点都叠加到该地区的卫星底层数据上,并对不同的水体、水稻生育期、调查地点的蚊虫滋生情况进行了方差分析。结果显示,由于Ikonos只有可见光和近红外光谱分辨能力,单一的Ikonos卫星数据难以区分不同样点和分层的生境,而QuickBird具有全光谱分辨能力,可区分所有的稻田生境。因此,可根据QuickBird0.6m卫星数据的土地利用和覆盖指数和阿拉伯按蚊滋生点幼虫的增殖特性,在当地建立和应用媒介综合防治系统(IVM-Integrated Vector Management)。