Rapid spread of double East- and West-African kdr mutations in wild Anopheles coluzzi from Côte d’Ivoire [version 1; peer review: 2 approved]

Malaria morbidity and mortality rates in Sub-Saharan Africa are increasing. The scale-up of long-lasting insecticidal nets and indoor residual spraying have been the major contributors to the decrease of malaria burden. These tools are now threatened by insecticide resistance in malaria vectors, which is spreading dramatically. After two different real-time polymerase chain reaction molecular characterizations carried out on 70 mosquitoes sampled in the locality of Elibou in southern Côte d’Ivoire, results revealed that 9 mosquitoes from Anopheles coluzzi harbored the double East- and West-African knockdown resistance mutations. In the previous year, only 1 mosquito out of 150 sampled from 10 regions of the country had the same genotype. These results show the rapid spread of insecticide resistance in malaria vectors and highlight the urgent need to diversify the methods of vector control in order to avoid the failure of insecticide-based vector control tools which may favor malaria fatalities

Effectiveness of community-based burden estimation to achieve elimination of lymphatic filariasis: A comparative cross-sectional investigation in Côte d’Ivoire

For lymphatic filariasis (LF) elimination, endemic countries must document the burden of LF morbidity (LFM). Community-based screening (CBS) is used to collect morbidity data, but evidence demonstrating its reliability is limited. Recent pilots of CBS for LFM alongside mass drug administration (MDA) in Côte d’Ivoire suggested low LFM prevalence (2.1–2.2 per 10,000). We estimated LFM prevalence in Bongouanou District, Côte d’Ivoire, using a comparative cross-sectional design. We compared CBS implemented independently of MDA, adapted from existing Ministry of Health protocols, to a population-based prevalence survey led by formally trained nurses. We evaluated the reliability of case identification, coverage, equity, and cost of CBS. CBS identified 87.4 cases of LFM per 10,000; the survey identified 47.5 (39.4–56.3; prevalence ratio [PR] 1.84; 95% CI 1.64–2.07). CBS identified 39.7 cases of suspect lymphoedema per 10,000; the survey confirmed 35.1 (29.2–41.5) filarial lymphoedema cases per 10,000 (PR 1.13 [0.98–1.31]). CBS identified 96.5 scrotal swellings per 10,000; the survey found 91.3 (83.2–99.8; PR 1.06 [0.93–1.21]); including 33.9 (27.7–38.8) filarial hydrocoele per 10,000 (PR of suspect to confirmed hydrocele 2.93 [2.46–3.55]). Positive predictive values for case identification through CBS were 65.0% (55.8–73.5%) for filarial lymphoedema; 93.7% (89.3–96.7%) for scrotal swellings; and 34.0% (27.3–41.2%) for filarial hydrocoele. Households of lower socioeconomic status and certain minority languages were at risk of exclusion. Direct financial costs were $0.17 per individual targeted and$69.62 per case confirmed. Our community-based approach to LFM burden estimation appears scalable and provided reliable prevalence estimates for LFM, scrotal swellings and LF-lymphoedema. The results represent a step-change improvement on CBS integrated with MDA, whilst remaining at programmatically feasible costs. Filarial hydrocoele cases were overestimated, attributable to the use of case definitions suitable for mass-screening by informal staff. Our findings are broadly applicable to countries aiming for LF elimination using CBS. The abstract is available in French in the S1 File.</jats:p

Comparison of Different Sampling Methods to Catch Lymphatic Filariasis Vectors in a Sudan Savannah Area of Mali

There is a need for better tools to monitor the transmission of lymphatic filariasis and malaria in areas undergoing interventions to interrupt transmission. Therefore, mosquito collection methods other than human landing catch (HLC) are needed. This study aimed to compare the Ifakara tent trap type C (ITTC) and the Biogents sentinel trap (BGST) to the HLC in areas with different vector densities. Mosquitoes were collected in two villages in Mali from July to December in 2011 and 2012. The three methods were implemented at each site with one ITTC, one BGST, and one HLC unit that consisted of one room with two collectors—one indoor and the other outdoor. The Anopheles collected in 2011 were individually dissected, whereas those from 2012 were screened in pools using reverse transcription-polymerase chain reaction (RT-PCR) to determine the maximum infection prevalence likelihood (MIPL) for Wuchereria bancrofti and Plasmodium falciparum. The dissection of the females also allowed to assess the parity rates, as well its results. Over the 2 years, the HLC method collected 1,019 Anopheles, yields that were 34- and 1.5-fold higher than those with the BGST and ITTC, respectively. None of the dissected Anopheles were infected. The RT-PCR results showed comparable MIPL between HLC and ITTC for W. bancrofti with one infected pool from each trap’s yield (respectively 0.03% [0.0009–0.2%] and 0.04% [0.001–0.2%]). For P. falciparum, no infected pool was recovered from BGST. The ITTC is a good alternative to HLC for xenomonitoring of program activities

Integration of LF morbidity management and disability prevention (MMDP) into community health services: exploring the coverage and equity of community health worker-driven LF MMDP burden assessment and service uptake in Côte d’Ivoire

This study tested the reliability of community health worker (CHW)-led lymphatic filariasis morbidity (LFM) burden estimates by having CHWs first estimate LFM burden, followed by a rigorous population-based survey to provide a representative estimate of LFM burden for the district. The study examined the accuracy of case identification by CHWs, social biases of CHWs that may prevent equitable care delivery, and the cost of the CHW burden estimation. The availability of morbidity management and disability prevention (MMDP) services was also surveyed in a comprehensive health facility-based survey covering all government owned health facilities in the district. Programs need a feasible and reliable method for LFM burden estimation and strategies to ensure that people have access to care. This study addresses the two pillars of WHO dossier development for LF MMDP, and will provide the Ministry of Health with essential information to plan and adapt their program to accommodate MMDP services. (2022-06-15

Financial costs of CDD screening activity, per person targeted and by case confirmed (total and by phase).

(PNG)</p

Predictors of household inclusion in community case search.

Predictors of household inclusion in community case search.</p

Map of the study area.

Population density data is from the Worldpop project: Linard C, Gilbert M, Snow RW, Noor AM, Tatem AJ. Population distribution, settlement patterns and accessibility across Africa in 2010. PloS one. 2012;7(2):e31743, www.worldpop.org [accessed 03/10/2020]. Base-map contains district and subdistrict boundaries from United Nations Office for the Coordination of Humanitarian Affairs (OCHA): (Côte d’Ivoire—Subnational Administrative Boundaries. 2019.), accessed 16/01/2022, roads from OpenStreetMap: HOTOSM Côte d’Ivoire Roads (OpenStreetMap Export), accessed via the Humanitarian Data Exchange website, and georeferenced health facility locations: Maina J, Ouma PO, Macharia PM, Alegana VA, Mitto B, Fall IS, et al. A spatial database of health facilities managed by the public health sector in sub Saharan Africa. Scientific data. 2019;6(1):1–8. (TIF)</p

Fig 1 -

Prevalence (number of cases per 10,000 population) of 1) lymphatic filariasis morbidity, 2) filarial lymphoedema, and 3) hydrocoele, detected through A) community-based screening led by volunteers and B) population-based prevalence survey led by formally trained nurses in Bongouanou, Côte d’Ivoire. Base-map contains district boundaries from the United Nations Office for the Coordination of Humanitarian Affairs (OCHA) {Affairs, 2019 #164}.</p

Demographic and clinical characteristics of confirmed cases of lymphatic filariasis morbidity identified.

(DOCX)</p

Candidate predictors and sources assessed for inclusion in mixed-effects generalized linear model of inclusion in household screening.

(DOCX)</p