Arbovirus transmission by Aedes mosquitoes has long been a significant problem in Africa. In West Africa, Aedes vector management faces significant challenges; lack of recent Aedes distributional data and potential distributional modeling hinder effective vector control and pose serious public health issues. In this study, larval and adult mosquitoes were collected from four study sites in Enugu State, Nigeria every other month between November 2017 and September 2018. A total number of 2997 Aedes mosquitoes were collected and identified, and 59 positive field occurrence points for both Aedes adult and larvae were recorded. A total of 18 positive occurrence points were used for modeling. Ecological Niche Models (ENMs) were used to estimate the current geographic distribution of Aedes species ( spp. ) in Enugu State, south-east Nigeria, and mosquito presence was used as a proxy for predicting risk of disease transmission. Maximum Entropy distribution modeling or “MaxEnt” was used for predicting the potential suitable habitats, using a portion of the occurrence records. A total of 23 environmental variables (19 bioclimatic and four topographic) were used to model the potential geographical distribution area under current climatic conditions. The most suitable habitat for Aedes spp. was predicted in the northern, central, and southeastern parts of Enugu State with some extensions in Anambra, Delta, and Edo States in the west, and Ebonyi State in the east. Seasonal temperature, precipitation of the wettest month, mean monthly temperature range, elevation, and precipitation of the driest months were the highest estimated main variable contributions associated with the distribution of Aedes spp. We found that Aedes spp. prefer to be situated in environmental conditions where precipitation of wettest month ranged from 265 to 330 mm, precipitation of driest quarter ranged from 25 to 75 mm while precipitation of wettest quarter ranged from 650 to 950 mm. Aedes mosquitoes, such as Ae. aegypti and Ae. albopictus, pose a significant threat to human health, hence, the results of this study will help decision makers to monitor the distribution of these species and establish a management plan for future national mosquito surveillance and control programs in Nigeria.

Malaria infection is a serious public health problem throughout Liberia, but vector surveillance is limited or nonexistent in remote regions of the country. To better understand the spatial and temporal distribution of malaria vectors in Liberia and to support vector and malaria activities of the Liberian Ministry of Health, a study was conducted to determine the efficacy of light traps baited with a synthetic lure and CO2 for capturing Anopheles gambiae sensu lato (Giles). Traps with a ultraviolet, light-emitting diode, and incandescent lights baited with a synthetic skin lure and CO2 combinations were evaluated at four field sites in three counties of Liberia for five consecutive nights every 8 wk during 2011. In total, 4,788 mosquitoes representing 56 species from nine genera were collected throughout the 30-wk study; An. gambiae s. l. comprised 32% and of the148 An. gambiae s. s. collected, 85% were of the S form. A greater percentage of An. gambiae s. l. were collected in ultraviolet traps baited with a synthetic lure and CO2 compared with any other trap configuration. The influence of trap configuration on conclusions from surveillance efforts, specifically with regards to An. gambiae is discussed.

Members of the Anopheles gambiae sensu lato (Giles) complex define a group of seven morphologically indistinguishable species, including the principal malaria vectors in Sub-Saharan Africa. Members of this complex differ in behavior and ability to transmit malaria; hence, precise identification of member species is critical to monitoring and evaluating malaria threat levels. We collected mosquitoes from five counties in Liberia every other month from May 2011 until May 2012, using various trapping techniques. A. gambiae complex members were identified using molecular techniques based on differences in the ribosomal DNA (rDNA) region between species and the molecular forms (S and M) of A. gambiae sensu stricto (s.s) specimens. In total, 1,696 A. gambiae mosquitoes were collected and identified. DNA was extracted from legs of each specimen with species identification determined by multiplex polymerase chain reaction using specific primers. The molecular forms (M or S) of A. gambiae s.s were determined by restriction fragment length polymorphism. Bivariate and multivariate logistic regression models identified environmental variables associated with genomic differentiation. Our results indicate widespread occurrence of A. gambiae s.s., the principal malaria vector in the complex, although two Anopheles melas Theobald/A. merus Donitz mosquitoes were detected. We found 72.6, 25.5, and 1.9% of A. gambiae s.s specimens were S, M, and hybrid forms, respectively. Statistical analysis indicates that the S form was more likely to be found in rural areas during rainy seasons and indoor catchments. This information will enhance vector control efforts in Liberia.

Pyrethroids are the most commonly used insecticides in the vector control programs. This insecticide group is one of the common recommended groups by the World Health Organization (WHO) for mosquito control. Recently, Pyrethroid resistance had rapidly spread worldwide which had its consequences on the effectiveness of control programs and threats public health. In this study, selection of Pyrethroid resistance in field-collected population of Culex pipiens was monitored after exposed to 0.05% Lambda-cyhalothrin for multiple generations. Activities of three detoxification enzymes namely; Oxidases, Nonspecific Esterases and Glutathione-S-transferases (GST), that synchronized with the resistance development, were monitored. Enzyme activities showed proportional relationship to Pyrethroid resistance. The results presented in this study will elucidate the Pyrethroid resistance development and its relation to the metabolic mechanisms. This may explain the complexity of resistance mechanisms in vector management and help to mitigate control failure due to insecticide resistance.

A nopheles stephensi mosquitoes, an urban malaria vector, have established robust populations in the Horn of Africa. Since the mosquito's detection in 2012 (1), malaria cases in Djibouti increased 42.9-fold during 2013-2021, reaching ≈72,300 cases (2). Before introduction of An. stephensi mosquitoes, Djibouti was approaching the preelimination phase for malaria (3). Because An. stephensi mosquitoes are competent vectors for Plasmodium falciparum and P. vivax parasites (3), WHO considers this mosquito species a major threat to malaria elimination in Africa (4). An. stephensi mosquitoes have also been detected in Sudan, Ethiopia,. Understanding An. stephensi mosquito adaptation to environmental conditions affecting population dynamics in urban settings is crucial in Africa. An. stephensi mosquitoes abundance (number of mosquitoes collected per trap night) changed from seasonal during fall-spring 2013-2016 to year-round in 2017 (3). Since An. stephensi mosquitoes were introduced, malaria cases have increased among military personnel, some immunologically naive, deployed as members of multinational militaries in Djibouti (9). Camp Lemonnier (CLDJ), a US naval base, has urban characteristics similar to the city of Djibouti, in which it is located. For this study, we monitored vector dynamics on the base, providing data to help inform health protection strategies among both military and civilian populations. The StudyIn coordination with the CLDJ Expeditionary Medical Facility, during January 2018-April 2021, we conducted weekly mosquito surveillance at 32 on-base sites covering 2 km 2 and stored information in dataset A. In October 2019, we began identifying monthly captures of An. stephensi mosquitoes specifically (i.e., identified at the species level) (dataset B). We set US Centers for Disease Control and Prevention (CDC) CO 2 -baited Miniature Light traps (https://www. cdc.gov/mosquitoes/guidelines/west-nile/surveillance/environmental-surveillance.html) and Woodstream Mosquito Magnet (MM) propane-generated CO 2 traps (https://www.woodstream.com) overnight near dwellings, dining areas, sport facilities, and other areas frequented by humans. We identified Anopheles species on the basis of criteria published elsewhere (10,11). We analyzed abundance data in the context of specific weather events and seasonal climatic trends at the time of collection. We obtained meteorologic data from several sources (Appendix, https://wwwnc.cdc.gov/EID/article/29/4/22-0549-App1.pdf), using latitude 11.54733 N and longitude 43.15948 E (0.6-1.2 km from study sites) for location and a locally appropriate meteorologic calendar to determine seasons. We assessed the effects on An. stephensi mosquito abundance of monthly mean temperatures and rainfall amounts at time of precipitation and at 2-week, and 1-and 2-month lag times (i.e., time after rainfall). We did not consider longer lag times because of the likely effects of evaporation.