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Odufuwa OG, Bradley J, Ngonyani S, Mpelepele AB, Matanila I, Muganga JB, Bosselmann R, Skovmand O, Mboma ZM, Moore SJ. Time of exposure and assessment influence the mortality induced by insecticides against metabolic resistant mosquitoes. Parasit Vectors 2024; 17:103. [PMID: 38431631 PMCID: PMC10908098 DOI: 10.1186/s13071-024-06190-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 02/09/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND Increasing metabolic resistance in malaria vector mosquitoes resulted in the development of insecticide-treated nets (ITNs) with active ingredients (AI) that target them. Bioassays that accurately measure the mortality induced by these AIs on ITNs are needed. Mosquito metabolic enzyme expression follows a circadian rhythm. Thus, this study assessed (i) influence of the time of day of mosquito exposure and (ii) timing of assessment of mortality post exposure (24 and 72 h) to ITNs against vectors that are susceptible to pyrethroids and those with metabolic and knockdown resistance mechanisms. METHODS Two cone bioassay experiments were conducted following World Health Organization (WHO) guidelines. Firstly, on ITNs incorporated with 2 g AI/kg of deltamethrin (DM) alone, or combined with 8 g AI/kg piperonyl butoxide (PBO) synergist, during the day (9:00-14:00 h) and repeated in the evening (18:00-20:00 h). This was followed by a confirmatory experiment during the afternoon (12:00-14:00 h) and repeated in the night (22:00-24:00 h) using mosquitoes unexposed or pre-exposed to PBO for 1 h before exposure to DM ITNs. Each net piece was tested with a minimum of eight cones per time (N = 24). The outcome was mortality after 24 h (M24) or 72 h (M72) of holding. RESULTS The cone bioassays performed using metabolic resistant mosquitoes during the evening showed significantly lower M24 than those performed in the day for DM: odds ratio (OR) 0.14 [95% confidence interval (CI) 0.06-0.30, p < 0.0001] and DM PBO [OR 0.29 (95% CI 0.18-0.49, p < 0.0001). M72 was higher than M24 for metabolic resistant mosquitoes exposed to DM [OR 1.44 (95% CI 1.09-1.88), p = 0.009] and DM PBO [OR 1.82 (95% CI 1.42-2.34), p < 0.0001]. An influence of hour of experiment and time of assessment was not observed for mosquitoes that had knockdown resistance or that were pyrethroid-susceptible. CONCLUSIONS Time of day of experiment and hour of assessment of delayed mortality after exposure of mosquitoes are important considerations in evaluating insecticides that interact with mosquito metabolism to counter metabolic resistant mosquitoes. This is important when evaluating field-aged ITNs that may have lower concentrations of AI.
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Affiliation(s)
- Olukayode G Odufuwa
- Vector Control Product Testing Unit (VCPTU) Ifakara Health Institute, Environmental Health, and Ecological Sciences, P.O. Box 74, Bagamoyo, Tanzania.
- Vector Biology Unit, Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Kreuzstrasse 2, Allschwill, 4123, Basel, Switzerland.
- Faculty of Science, University of Basel, Petersplatz 1, 4001, Basel, Switzerland.
- MRC International Statistics and Epidemiology Group, London School of Hygiene and Tropical Medicine (LSHTM), London, WC1E 7HT, UK.
| | - John Bradley
- MRC International Statistics and Epidemiology Group, London School of Hygiene and Tropical Medicine (LSHTM), London, WC1E 7HT, UK
| | - Safina Ngonyani
- Vector Control Product Testing Unit (VCPTU) Ifakara Health Institute, Environmental Health, and Ecological Sciences, P.O. Box 74, Bagamoyo, Tanzania
| | - Ahmadi Bakari Mpelepele
- Vector Control Product Testing Unit (VCPTU) Ifakara Health Institute, Environmental Health, and Ecological Sciences, P.O. Box 74, Bagamoyo, Tanzania
| | - Isaya Matanila
- Vector Control Product Testing Unit (VCPTU) Ifakara Health Institute, Environmental Health, and Ecological Sciences, P.O. Box 74, Bagamoyo, Tanzania
| | - Joseph B Muganga
- Vector Control Product Testing Unit (VCPTU) Ifakara Health Institute, Environmental Health, and Ecological Sciences, P.O. Box 74, Bagamoyo, Tanzania
| | | | | | - Zawadi Mageni Mboma
- Vector Control Product Testing Unit (VCPTU) Ifakara Health Institute, Environmental Health, and Ecological Sciences, P.O. Box 74, Bagamoyo, Tanzania
- The Nelson Mandela African Institution of Science and Technology (NM-AIST), Tengeru, P.O. Box 447, Arusha, Tanzania
| | - Sarah Jane Moore
- Vector Control Product Testing Unit (VCPTU) Ifakara Health Institute, Environmental Health, and Ecological Sciences, P.O. Box 74, Bagamoyo, Tanzania
- Vector Biology Unit, Department of Epidemiology and Public Health, Swiss Tropical & Public Health Institute, Kreuzstrasse 2, Allschwill, 4123, Basel, Switzerland
- Faculty of Science, University of Basel, Petersplatz 1, 4001, Basel, Switzerland
- The Nelson Mandela African Institution of Science and Technology (NM-AIST), Tengeru, P.O. Box 447, Arusha, Tanzania
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Namango IH, Marshall C, Saddler A, Ross A, Kaftan D, Tenywa F, Makungwa N, Odufuwa OG, Ligema G, Ngonyani H, Matanila I, Bharmal J, Moore J, Moore SJ, Hetzel MW. The Centres for Disease Control light trap (CDC-LT) and the human decoy trap (HDT) compared to the human landing catch (HLC) for measuring Anopheles biting in rural Tanzania. Malar J 2022; 21:181. [PMID: 35690745 PMCID: PMC9188237 DOI: 10.1186/s12936-022-04192-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Accepted: 05/20/2022] [Indexed: 11/10/2022] Open
Abstract
Background Vector mosquito biting intensity is an important measure to understand malaria transmission. Human landing catch (HLC) is an effective but labour-intensive, expensive, and potentially hazardous entomological surveillance tool. The Centres for Disease Control light trap (CDC-LT) and the human decoy trap (HDT) are exposure-free alternatives. This study compared the CDC-LT and HDT against HLC for measuring Anopheles biting in rural Tanzania and assessed their suitability as HLC proxies. Methods Indoor mosquito surveys using HLC and CDC-LT and outdoor surveys using HLC and HDT were conducted in 2017 and in 2019 in Ulanga, Tanzania in 19 villages, with one trap/house/night. Species composition, sporozoite rates and density/trap/night were compared. Aggregating the data by village and month, the Bland–Altman approach was used to assess agreement between trap types. Results Overall, 66,807 Anopheles funestus and 14,606 Anopheles arabiensis adult females were caught with 6,013 CDC-LT, 339 indoor-HLC, 136 HDT and 195 outdoor-HLC collections. Indoors, CDC-LT caught fewer An. arabiensis (Adjusted rate ratio [Adj.RR] = 0.35, 95% confidence interval [CI]: 0.27–0.46, p < 0.001) and An. funestus (Adj.RR = 0.63, 95%CI: 0.51–0.79, p < 0.001) than HLC per trap/night. Outdoors, HDT caught fewer An. arabiensis (Adj.RR = 0.04, 95%CI: 0.01–0.14, p < 0.001) and An. funestus (Adj.RR = 0.10, 95%CI: 0.07–0.15, p < 0.001) than HLC. The bias and variability in number of mosquitoes caught by the different traps were dependent on mosquito densities. The relative efficacies of both CDC-LT and HDT in comparison to HLC declined with increased mosquito abundance. The variability in the ratios was substantial for low HLC counts and decreased as mosquito abundance increased. The numbers of sporozoite positive mosquitoes were low for all traps. Conclusions CDC-LT can be suitable for comparing mosquito populations between study arms or over time if accuracy in the absolute biting rate, compared to HLC, is not required. CDC-LT is useful for estimating sporozoite rates because large numbers of traps can be deployed to collect adequate mosquito samples. The present design of the HDT is not amenable for use in large-scale entomological surveys. Use of HLC remains important for estimating human exposure to mosquitoes as part of estimating the entomological inoculation rate (EIR). Supplementary Information The online version contains supplementary material available at 10.1186/s12936-022-04192-9.
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Affiliation(s)
- Isaac Haggai Namango
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland. .,University of Basel, Basel, Switzerland. .,Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania.
| | - Carly Marshall
- Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania.,British Columbia Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada
| | - Adam Saddler
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland.,Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania.,Telethon Kids Institute, Perth, Australia
| | - Amanda Ross
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland.,University of Basel, Basel, Switzerland
| | - David Kaftan
- Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania.,New York University Grossman School of Medicine, New York, NY, USA
| | - Frank Tenywa
- Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania
| | - Noely Makungwa
- Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania
| | - Olukayode G Odufuwa
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland.,University of Basel, Basel, Switzerland.,Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania.,London School of Hygiene and Tropical Medicine, London, UK
| | - Godfrey Ligema
- Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania
| | - Hassan Ngonyani
- Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania
| | - Isaya Matanila
- Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania
| | - Jameel Bharmal
- Innovative Vector Control Consortium, Dar es Salaam, Tanzania
| | - Jason Moore
- Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania
| | - Sarah J Moore
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland.,University of Basel, Basel, Switzerland.,Vector Control Product Testing Unit, Ifakara Health Institute, Bagamoyo, Tanzania.,Nelson Mandela African Institute of Science and Technology, Arusha, Tanzania
| | - Manuel W Hetzel
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland.,University of Basel, Basel, Switzerland
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