Insecticide resistance in Anopheles arabiensis from Ethiopia (2012-2016): a nationwide study for insecticide resistance monitoring.

BACKGROUND: Indoor residual spraying (IRS) and long-lasting insecticidal nets (LLINs) remain the cornerstones of malaria vector control. However, the development of insecticide resistance and its implications for operational failure of preventative strategies are of concern. The aim of this study was to characterize insecticide resistance among Anopheles arabiensis populations in Ethiopia and describe temporal and spatial patterns of resistance between 2012 and 2016. METHODS: Between 2012 and 2016, resistance status of An. arabiensis was assessed annually during the long rainy seasons in study sites from seven of the nine regions in Ethiopia. Insecticide resistance levels were measured with WHO susceptibility tests and CDC bottle bioassays using insecticides from four chemical classes (organochlorines, pyrethroids, organophosphates and carbamates), with minor variations in insecticides tested and assays conducted between years. In selected sites, CDC synergist assays were performed by pre-exposing mosquitoes to piperonyl butoxide (PBO). In 2015 and 2016, mosquitoes from DDT and deltamethrin bioassays were randomly selected, identified to species-level and screened for knockdown resistance (kdr) by PCR. RESULTS: Intense resistance to DDT and pyrethroids was pervasive across Ethiopia, consistent with historic use of DDT for IRS and concomitant increases in insecticide-treated net coverage over the last 15 years. Longitudinal resistance trends to malathion, bendiocarb, propoxur and pirimiphos-methyl corresponded to shifts in the national insecticide policy. By 2016, resistance to the latter two insecticides had emerged, with the potential to jeopardize future long-term effectiveness of vector control activities in these areas. Between 2015 and 2016, the West African (L1014F) kdr allele was detected in 74.1% (n = 686/926) of specimens, with frequencies ranging from 31 to 100% and 33 to 100% in survivors from DDT and deltamethrin bioassays, respectively. Restoration of mosquito susceptibility, following pre-exposure to PBO, along with a lack of association between kdr allele frequency and An. arabiensis mortality rate, both indicate metabolic and target-site mutation mechanisms are contributing to insecticide resistance. CONCLUSIONS: Data generated by this study will strengthen the National Malaria Control Programme's insecticide resistance management strategy to safeguard continued efficacy of IRS and other malaria control methods in Ethiopia

Evidence for a role of Anopheles stephensi in the spread of drug- and diagnosis-resistant malaria in Africa

Anopheles stephensi, an Asian malaria vector, continues to expand across Africa. The vector is now firmly established in urban settings in the Horn of Africa. Its presence in areas where malaria resurged suggested a possible role in causing malaria outbreaks. Here, using a prospective case-control design, we investigated the role of An. stephensi in transmission following a malaria outbreak in Dire Dawa, Ethiopia in April-July 2022. Screening contacts of patients with malaria and febrile controls revealed spatial clustering of Plasmodium falciparum infections around patients with malaria in strong association with the presence of An. stephensi in the household vicinity. Plasmodium sporozoites were detected in these mosquitoes. This outbreak involved clonal propagation of parasites with molecular signatures of artemisinin and diagnostic resistance. To our knowledge, this study provides the strongest evidence so far for a role of An. stephensi in driving an urban malaria outbreak in Africa, highlighting the major public health threat posed by this fast-spreading mosquito

Time series analysis of trends in malaria cases and deaths at hospitals and the effect of antimalarial interventions, 2001-2011, Ethiopia.

The Government of Ethiopia and its partners have deployed artemisinin-based combination therapies (ACT) since 2004 and long-lasting insecticidal nets (LLINs) since 2005. Malaria interventions and trends in malaria cases and deaths were assessed at hospitals in malaria transmission areas during 2001-2011.Regional LLINs distribution records were used to estimate the proportion of the population-at-risk protected by LLINs. Hospital records were reviewed to estimate ACT availability. Time-series analysis was applied to data from 41 hospitals in malaria risk areas to assess trends of malaria cases and deaths during pre-intervention (2001-2005) and post-interventions (2006-2011) periods.The proportion of the population-at-risk potentially protected by LLINs increased to 51% in 2011. The proportion of facilities with ACTs in stock exceeded 87% during 2006-2011. Among all ages, confirmed malaria cases in 2011 declined by 66% (95% confidence interval [CI], 44-79%) and SPR by 37% (CI, 20%-51%) compared to the level predicted by pre-intervention trends. In children under 5 years of age, malaria admissions and deaths fell by 81% (CI, 47%-94%) and 73% (CI, 48%-86%) respectively. Optimal breakpoint of the trendlines occurred between January and June 2006, consistent with the timing of malaria interventions. Over the same period, non-malaria cases and deaths either increased or remained unchanged, the number of malaria diagnostic tests performed reflected the decline in malaria cases, and rainfall remained at levels supportive of malaria transmission.Malaria cases and deaths in Ethiopian hospitals decreased substantially during 2006-2011 in conjunction with scale-up of malaria interventions. The decrease could not be accounted for by changes in hospital visits, malaria diagnostic testing or rainfall. However, given the history of variable malaria transmission in Ethiopia, more data would be required to exclude the possibility that the decrease is due to other factors

MOESM1 of Insecticide resistance in Anopheles arabiensis from Ethiopia (2012-2016): a nationwide study for insecticide resistance monitoring

Tables S1. Summary of PMI-supported IRS activities in Ethiopia, 2008-2016. Table S2. Summary of insecticide resistance assays conducted per year in Ethiopia, 2012-2016. Table S3. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in WHO susceptibility tests conducted in Ethiopia, 2013. Table S4. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in WHO susceptibility tests conducted in Ethiopia, 2014. Table S5. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in WHO susceptibility tests conducted in Ethiopia, 2015. Table S6. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in WHO susceptibility tests conducted in Ethiopia, 2016. Table S7. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in CDC bottle bioassays conducted in Ethiopia, 2013. Table S8. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in CDC bottle bioassays conducted in Ethiopia, 2014. Table S9. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in CDC bottle bioassays conducted in Ethiopia, 2015. Table S10. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in CDC bottle bioassays conducted in Ethiopia, 2016. Table S11. Percentage corrected mortality (and numbers tested) of Anopheles arabiensis in WHO susceptibility tests and CDC bottle bioassays conducted in Ziway Dugda, Ethiopia, 2013-2016

Administrative regions and areas below and above 2000 meters elevation in Ethiopia.

<p>Administrative regions and areas below and above 2000 meters elevation in Ethiopia.</p

Percentage of population potentially protected with LLINs*, IRS and percentage of health facilities with stock of ACT available by year, 2001–2011, Ethiopia (*number of LLINs distributed during the 3 year period ×1.8/population).

<p>Percentage of population potentially protected with LLINs*, IRS and percentage of health facilities with stock of ACT available by year, 2001–2011, Ethiopia (*number of LLINs distributed during the 3 year period ×1.8/population).</p

Time series of monthly confirmed malaria cases, slide positivity rate, admissions and deaths extracted by use of a Hodrick-Prescott filter with monthly smoothing parameter λ = 14,400 (HP = Hodrick-Prescott filter; MAl-IPDAll Ages = Inpatient malaria cases in all ages; Mal-DeathsAll Ages = Malaria deaths in all ages, SPRAll Ages = Slide positivity rate in all ages; PositiveAll ages = Number of confirmed cases).

<p>Time series of monthly confirmed malaria cases, slide positivity rate, admissions and deaths extracted by use of a Hodrick-Prescott filter with monthly smoothing parameter λ = 14,400 (HP  =  Hodrick-Prescott filter; MAl-IPDAll Ages  =  Inpatient malaria cases in all ages; Mal-DeathsAll Ages  =  Malaria deaths in all ages, SPRAll Ages  =  Slide positivity rate in all ages; PositiveAll ages  =  Number of confirmed cases).</p

Percentage change in inpatient malaria cases, malaria deaths and slide positivity rate in 2011 compared to pre-intervention period (2001–2005), by hospital and region, in 41 hospitals below 2000 m elevation, Ethiopia, 2001–2011.

<p><i>A negative percentage indicates a decrease of the indicator or impact in the year compared to baseline.</i></p><p>Percentage change in inpatient malaria cases, malaria deaths and slide positivity rate in 2011 compared to pre-intervention period (2001–2005), by hospital and region, in 41 hospitals below 2000 m elevation, Ethiopia, 2001–2011.</p

Percentage change in malaria and non-malaria related indicators post-intervention years compared to pre-intervention period (2001–2005), by age, 41 hospitals <2000 m elevation, Ethiopia, 2001–2011.

<p><i>A negative percentage (ratio between observed and predicted indicators level multiplied by 100) indicates a decrease se in the indicator in the year compared to baseline period</i>.</p><p><i>A positive percentage indicate an increase of the indicator or impact in the year compared to baseline</i>.</p>†<p><i>: 95% Confidence Interval (CI) does not include zero and change of trend (pre versus post-intervention) is statistically significant</i>.</p><p>Percentage change in malaria and non-malaria related indicators post-intervention years compared to pre-intervention period (2001–2005), by age, 41 hospitals <2000 m elevation, Ethiopia, 2001–2011.</p