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Cited by 163Malaria Research and ControlBird parasitology and diseasesMosquito-borne diseases and control

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

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Emiru, Tadele, Getachew, Dejene, Murphy, Maxwell, Sedda, Luigi, Ejigu, Legesse Alamerie, Bulto, Mikiyas Gebremichael, Byrne, Isabel, Demisse, Mulugeta, Abdo, Melat, Chali, Wakweya, Elliott, Aaron, Vickers, Eric Neubauer, Aranda-Díaz, Andrés, Alemayehu, Lina, Behaksera, Sinknesh W., Jebessa, Gutema, Dinka, Hunduma, Tsegaye, Tizita, Teka, Hiwot, Chibsa, Sheleme, Mumba, Peter, Girma, Samuel, Hwang, Jimee, Yoshimizu, Melissa, Sutcliffe, Alice, Taffese, Hiwot Solomon, Bayissa, Gudissa Aseffa, Zohdy, Sarah, Tongren, Jon Eric, Drakeley, Chris, Greenhouse, Bryan, Bousema, Teun, Tadesse, Fitsum G.·2023·Nature Medicine
DOI 10.1038/s41591-023-02641-9PMC PMC10719088

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Abstract

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.

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Fig. 1 Global distribution of An. stephensi and the study location. a, The global distribution of An. stephensi where it is native (blue) and invasive (red) is shown, together with sporozoite infection detection outcomes where it was found infected and not infected with P. falciparum (Pf) and P. vivax (Pv). Sites where An. stephensi was observed but mosquitoes were not tested for the presence of sporozoites are also shown (not determined). Settings where dedicated entomological surveillance did not detect An. stephensi mosquitoes are indicated by gray circles (negative). b, The locations of case (red) and control (green) households/dormitories surveyed in this study are shown, together with water storage containers (black), water treatment plant (in the university campus), health facilities (H) and Butiji River in Dire Dawa City. Source: the global map (a) was modified on the basis of the malaria threats map7 of the WHO. Source data
Fig. 1 Global distribution of An. stephensi and the study location. a, The global distribution of An. stephensi where it is native (blue) and invasive (red) is shown, together with sporozoite infection detection outcomes where it was found infected and not infected with P. falciparum (Pf) and P. vivax (Pv). Sites where An. stephensi was observed but mosquitoes were not tested for the presence of sporozoites are also shown (not determined). Settings where dedicated entomological surveillance did not detect An. stephensi mosquitoes are indicated by gray circles (negative). b, The locations of case (red) and control (green) households/dormitories surveyed in this study are shown, together with water storage containers (black), water treatment plant (in the university campus), health facilities (H) and Butiji River in Dire Dawa City. Source: the global map (a) was modified on the basis of the malaria threats map7 of the WHO. Source dataCC BY · PubMed Central
Fig. 2 Temporal trends in malaria burden and parasite density distributions in Dire Dawa. a,b, Malaria trends using DHIS2 data (a) are shown, with the prevalence and odds of detecting additional infections in close contacts of cases compared with controls in Dire Dawa, separately for all close contacts, contacts in the city and the university (b). ORs were obtained from univariate logistic regression, with diagnostic test results as outcome and site as predictor. Univariate logistic models were fitted for each diagnostic test. ORs are shown on a log10 scale (x axis), together with their 95% CI bars and respective P values (estimated from Wald test). Numbers to the right of the forest plot indicate the proportion of positive cases by respective diagnostic test (color coded and embedded in the figure) among control and index household/dormitory members. c–e, Parasite density per microliter distributions and their respective averages determined by 18S-based qPCR among HRP2-based RDT-positive (n = 113) and RDT-negative (n = 88) infections (c) and microscopy-positive (n = 129) and microscopy-negative (n = 71) infections (d) are shown, together with distribution among index cases (n = 99), contacts of index cases (n = 61), controls (n = 14) and contacts of controls (n = 27) (e). Source data
Fig. 2 Temporal trends in malaria burden and parasite density distributions in Dire Dawa. a,b, Malaria trends using DHIS2 data (a) are shown, with the prevalence and odds of detecting additional infections in close contacts of cases compared with controls in Dire Dawa, separately for all close contacts, contacts in the city and the university (b). ORs were obtained from univariate logistic regression, with diagnostic test results as outcome and site as predictor. Univariate logistic models were fitted for each diagnostic test. ORs are shown on a log10 scale (x axis), together with their 95% CI bars and respective P values (estimated from Wald test). Numbers to the right of the forest plot indicate the proportion of positive cases by respective diagnostic test (color coded and embedded in the figure) among control and index household/dormitory members. c–e, Parasite density per microliter distributions and their respective averages determined by 18S-based qPCR among HRP2-based RDT-positive (n = 113) and RDT-negative (n = 88) infections (c) and microscopy-positive (n = 129) and microscopy-negative (n = 71) infections (d) are shown, together with distribution among index cases (n = 99), contacts of index cases (n = 61), controls (n = 14) and contacts of controls (n = 27) (e). Source dataCC BY · PubMed Central
Fig. 3 Spatial distribution and clustering of P. falciparum parasites and An. stephensi. a–c, Statistically significant evidence for global spatial clustering of household P. falciparum infections prevalence (a) and An. stephensi mosquitoes (b) and an overlap between the two (c) were observed. Eleven clusters of households were found (A) in the city (P < 0.05) by one-sided local Anselin Moran’s I test (pseudo P values calculated from 9,999 random permutations): high–high (n = 6) whereby households had high P. falciparum prevalence, low–low clusters (n = 5) whereby households had low P. falciparum prevalence, and high–low outlier clusters (n = 2) whereby high P. falciparum prevalence households were surrounded by low P. falciparum prevalence households, or vice versa. Locations of An. stephensi mosquitoes found infected (n = 3) are shown in dark-red circles and triangles (b). d,e, A map displaying case incidence colored by genetic cluster (lineage 1 in blue and lineage 2 in red) are shown along with timelines that cases were identified (d) and their spatial distribution (e). Source data
Fig. 3 Spatial distribution and clustering of P. falciparum parasites and An. stephensi. a–c, Statistically significant evidence for global spatial clustering of household P. falciparum infections prevalence (a) and An. stephensi mosquitoes (b) and an overlap between the two (c) were observed. Eleven clusters of households were found (A) in the city (P < 0.05) by one-sided local Anselin Moran’s I test (pseudo P values calculated from 9,999 random permutations): high–high (n = 6) whereby households had high P. falciparum prevalence, low–low clusters (n = 5) whereby households had low P. falciparum prevalence, and high–low outlier clusters (n = 2) whereby high P. falciparum prevalence households were surrounded by low P. falciparum prevalence households, or vice versa. Locations of An. stephensi mosquitoes found infected (n = 3) are shown in dark-red circles and triangles (b). d,e, A map displaying case incidence colored by genetic cluster (lineage 1 in blue and lineage 2 in red) are shown along with timelines that cases were identified (d) and their spatial distribution (e). Source dataCC BY · PubMed Central

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  1. Goldstein, H. & Browne, W. in Contemporary Psychometrics (eds Maydeu-Olivares, A. & McArdle, J. J.) Ch. 14 (Taylor & Francis Group, 2005).
  2. Burnham, K. P. & Anderson, D. R. (eds) Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach 2nd edn (Springer, 2002).

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Authors
Emiru, T., Getachew, D., Murphy, M., Sedda, L., Ejigu, L. A., Bulto, M. G., Byrne, I., Demisse, M., Abdo, M., Chali, W., Elliott, A., Vickers, E. N., Aranda-Díaz, A., Alemayehu, L., Behaksera, S. W., Jebessa, G., Dinka, H., Tsegaye, T., Teka, H., Chibsa, S., Mumba, P., Girma, S., Hwang, J., Yoshimizu, M., Sutcliffe, A., Taffese, H. S., Bayissa, G. A., Zohdy, S., Tongren, J. E., Drakeley, C., Greenhouse, B., Bousema, T., & Tadesse, F. G.
Affiliations
  • Armauer Hansen Research Institute (ET)
  • Adama Science and Technology University (ET)
  • University of California, San Francisco (US)
  • Lancaster University (GB)
  • London School of Hygiene & Tropical Medicine (GB)
  • Radboud University Medical Center (NL)
  • United States Agency for International Development (US)
  • Centers for Disease Control and Prevention (US)
  • Federal Ministry of Health (ET)
  • Radboud University Nijmegen (NL)
Corresponding author
Tadesse, Fitsum G.
ORCID
Venue
Nature Medicine
Publisher
Springer Science and Business Media LLC
Published
2023-10-26
Volume
29
Issue
12
Pages
3203-3211
ISSN
  • 1078-8956 (ISSN-L)
  • 1546-170X
DOI
10.1038/s41591-023-02641-9
PMC
PMC10719088
OpenAlex
W4387956265
Cited by
162
References
71
Citations by year
2026: 39 · 2025: 57 · 2024: 59 · 2023: 7
FWCI
41.47
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Medicine (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Lancaster EPrints (Lancaster University) (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
  • Radboud Repository (Radboud University) (submittedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (submittedVersion)
  • Greater South Information System
Funders
  • Bill and Melinda Gates Foundation (INV-005898, 005898, INV-035257)
  • Wellcome Trust (102348, 220870/Z/20/Z, 226350)
  • National Institute for Health and Care Research (220870/Z/20/Z)
  • Nederlandse Organisatie voor Wetenschappelijk Onderzoek (09150182210039)
  • National Institutes of Health
  • Centers for Disease Control and Prevention
  • National Institute of Allergy and Infectious Diseases (K24AI144048)
  • H2020 European Research Council (864180)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
  • Life Sciences › Immunology and Microbiology › Parasitology › Bird parasitology and diseases
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mosquito-borne diseases and control
Keywords
Anopheles stephensi, malaria transmission, Plasmodium falciparum, artemisinin resistance, malaria outbreak, urban malaria, vector range expansion, sporozoites, Dire Dawa
MeSH terms
Mosquito Vectors, Animals, Anopheles, Ethiopia, Humans, Malaria, Malaria, Falciparum

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