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13 results on '"Lerch, Anita"'

2. Inferring person-to-person networks of Plasmodium falciparum transmission: are analyses of routine surveillance data up to the task?

Author

Huber, John H, Hsiang, Michelle S, Dlamini, Nomcebo, Murphy, Maxwell, Vilakati, Sibonakaliso, Nhlabathi, Nomcebo, Lerch, Anita, Nielsen, Rasmus, Ntshalintshali, Nyasatu, Greenhouse, Bryan, and Perkins, T Alex

Subjects
Infectious Diseases, Vector-Borne Diseases, Malaria, Rare Diseases, Infection, Good Health and Well Being, Disease Outbreaks, Humans, Malaria, Falciparum, Plasmodium falciparum, Reproduction, Microbiology, Medical Microbiology, Public Health and Health Services, Tropical Medicine
Abstract

BackgroundInference of person-to-person transmission networks using surveillance data is increasingly used to estimate spatiotemporal patterns of pathogen transmission. Several data types can be used to inform transmission network inferences, yet the sensitivity of those inferences to different data types is not routinely evaluated.MethodsThe influence of different combinations of spatial, temporal, and travel-history data on transmission network inferences for Plasmodium falciparum malaria were evaluated.ResultsThe information content of these data types may be limited for inferring person-to-person transmission networks and may lead to an overestimate of transmission. Only when outbreaks were temporally focal or travel histories were accurate was the algorithm able to accurately estimate the reproduction number under control, Rc. Applying this approach to data from Eswatini indicated that inferences of Rc and spatiotemporal patterns therein depend upon the choice of data types and assumptions about travel-history data.ConclusionsThese results suggest that transmission network inferences made with routine malaria surveillance data should be interpreted with caution.

Published
2022

3. Projecting vaccine demand and impact for emerging zoonotic pathogens

Author

Lerch, Anita, ten Bosch, Quirine A., L’Azou Jackson, Maïna, Bettis, Alison A., Bernuzzi, Mauro, Murphy, Georgina A. V., Tran, Quan M., Huber, John H., Siraj, Amir S., Bron, Gebbiena M., Elliott, Margaret, Hartlage, Carson S., Koh, Sojung, Strimbu, Kathyrn, Walters, Magdalene, Perkins, T. Alex, and Moore, Sean M.

Published
2022
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6. Plasmodium falciparum transmission in the highlands of Ethiopia is driven by closely related and clonal parasites.

Author

Holzschuh, Aurel, Ewnetu, Yalemwork, Carlier, Lise, Lerch, Anita, Gerlovina, Inna, Baker, Sarah Cate, Yewhalaw, Delenasaw, Haileselassie, Werissaw, Berhane, Nega, Lemma, Wossenseged, and Koepfli, Cristian

Subjects
PLASMODIUM, PLASMODIUM falciparum, UPLANDS, NUCLEOTIDE sequencing, HUMAN migrations, PARASITES
Abstract

Malaria cases are frequently recorded in the Ethiopian highlands even at altitudes above 2000 m. The epidemiology of malaria in the Ethiopian highlands, and, in particular, the role of importation by human migration from the highly endemic lowlands is not well understood. We sequenced 187 Plasmodium falciparum samples from two sites in the Ethiopian highlands, Gondar (n = 159) and Ziway (n = 28), using a multiplexed droplet digital PCR (ddPCR)‐based amplicon sequencing method targeting 35 microhaplotypes and drug resistance loci. Here, we characterize the parasite population structure and genetic relatedness. We identify moderate parasite diversity (mean HE: 0.54) and low infection complexity (74.9% monoclonal). A significant percentage of infections share microhaplotypes, even across transmission seasons and sites, indicating persistent local transmission. We identify multiple clusters of clonal or near‐clonal infections, highlighting high genetic relatedness. Only 6.3% of individuals diagnosed with P. falciparum reported recent travel. Yet, in clonal or near‐clonal clusters, infections of travellers were frequently observed first in time, suggesting that parasites may have been imported and then transmitted locally. 31.1% of infections are pfhrp2‐deleted and 84.4% pfhrp3‐deleted, and 28.7% have pfhrp2/3 double deletions. Parasites with pfhrp2/3 deletions and wild‐type parasites are genetically distinct. Mutations associated with resistance to sulphadoxine–pyrimethamine or suggested to reduce sensitivity to lumefantrine are observed at near‐fixation. In conclusion, genomic data corroborate local transmission and the importance of intensified control in the Ethiopian highlands. [ABSTRACT FROM AUTHOR]

Published
2024
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8. Highly multiplexed ddPCR-amplicon sequencing reveals strongPlasmodium falciparumpopulation structure and isolated populations amenable to local elimination efforts in Zanzibar

Author

Holzschuh, Aurel, primary, Lerch, Anita, additional, Gerlovina, Inna, additional, Fakih, Bakar S., additional, Al-mafazy, Abdul-wahid H., additional, Reaves, Erik J., additional, Ali, Abdullah, additional, Abbas, Faiza, additional, Ali, Mohamed Haji, additional, Ali, Mohamed Ali, additional, Hetzel, Manuel W., additional, Yukich, Joshua, additional, and Koepfli, Cristian, additional

Published
2023
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9. Additional file 1 of Projecting vaccine demand and impact for emerging zoonotic pathogens

Author

Lerch, Anita, ten Bosch, Quirine A., L’Azou Jackson, Maïna, Bettis, Alison A., Bernuzzi, Mauro, Murphy, Georgina A. V., Tran, Quan M., Huber, John H., Siraj, Amir S., Bron, Gebbiena M., Elliott, Margaret, Hartlage, Carson S., Koh, Sojung, Strimbu, Kathyrn, Walters, Magdalene, Perkins, T. Alex, and Moore, Sean M.

Subjects
viruses, virus diseases
Abstract

Additional file 1: Table S1. Overview of data references. Table S2. Sizes of single reactive vaccination campaigns targeting the general population or healthcare workers (HCWs). SI Text. Sensitivity analysis and extended model limitations. Fig. S1. Spillover and reactive vaccination patterns for Lassa fever virus (LASV). Fig. S2. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV). Fig. S3. Spillover and reactive vaccination patterns for Nipah virus (NiV). Fig. S4. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV). Fig. S5. Vaccine regimens required for Lassa fever virus (LASV). Fig. S6. Vaccine regimens required for Middle Eastern respiratory virus (MERS-CoV). Fig. S7. Vaccine regimens required for Nipah virus (NiV). Fig. S8. Vaccine regimens required for Rift Valley fever virus (RVFV). Fig. S9. Vaccine regimens required to vaccinate healthcare workers for Lassa fever virus (LASV). Fig. S10. Vaccine regimens required to vaccinate healthcare workers for Middle Eastern respiratory virus (MERS-CoV). Fig. S11. Vaccine regimens required to vaccinate healthcare workers for Nipah virus (NiV). Fig. S12. Vaccine regimens required to vaccinate veterinarians for Rift Valley fever virus (RVFV). Fig. S13. Vaccination impact sensitivity analysis for LASV. Fig. S14. Vaccination impact sensitivity analysis for NiV. Fig. S15. Vaccination impact sensitivity analysis for RVFV. Fig. S16. Number of cases under different R0 assumptions. Fig. S17. Number of vaccine regimens required under different R0 assumptions. Fig. S18. Number of vaccine regimens required for healthcare workers (HCWs) under different R0 assumptions. Fig. S19. Number of cases averted by vaccinating the general population under different R0 assumptions. Fig. S20. Fraction of cases averted by vaccinating the general population under different R0 assumptions. Fig. S21. Number of cases averted per vaccine regimen administered to the general population under different R0 assumptions. Fig. S22. Number of cases averted per vaccine regimen administered to healthcare workers (HCWs) under different R0 assumptions. Fig. S23. Spillover and reactive vaccination patterns for Lassa fever virus (LASV) within adm1 catchment areas. Fig. S24. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV) within adm1 catchment areas. Fig. S25. Spillover and reactive vaccination patterns for Nipah virus (NiV) within adm1 catchment areas. Fig. S26. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV) within adm1 catchment areas. Fig. S27. Spillover and reactive vaccination patterns for Lassa fever virus (LASV) within adm1 hospital catchment areas. Fig. S28. Spillover and reactive vaccination patterns for Middle Eastern respiratory virus (MERS-CoV) within adm1 hospital catchment areas. Fig. S29. Spillover and reactive vaccination patterns for Nipah virus (NiV) within adm1 hospital catchment areas. Fig. S30. Spillover and reactive vaccination patterns for Rift Valley fever virus (RVFV) within adm1 hospital catchment areas. Fig. S31. Geographic distribution of spillover cases and reactive vaccination campaigns for adm1 catchment areas. Fig. S32. Geographic distribution of spillover cases and reactive vaccination campaigns for adm1 hospital catchment areas. Fig. S33. Annual cases and reactive vaccination impacts for adm1 catchment areas. Fig. S34. Annual cases and reactive vaccination impacts for adm1 hospital-based catchment areas.

Published
2022
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11. Protein Interaction Analysis of Plasmodium falciparum Circumsporozoite Protein Variants With Human Immunoproteins Explains RTS,S Vaccine Efficacy

Author

Dieng, Cheikh Cambel, primary, Ford, Colby T., additional, Lerch, Anita, additional, Doniou, Dickson, additional, Huynh, Jennifer, additional, Vegesna, Kovidh, additional, Guo, Jun-tao, additional, Janies, Daniel, additional, Amoah, Linda, additional, Afrane, Yaw, additional, and Lo, Eugenia, additional

Published
2022
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