TY - JOUR
T1 - Modelling the impact of interventions on imported, introduced and indigenous malaria infections in Zanzibar, Tanzania
AU - Das, Aatreyee M.
AU - Hetzel, Manuel W.
AU - Yukich, Joshua O.
AU - Stuck, Logan
AU - Fakih, Bakar S.
AU - Al-Mafazy, Abdul-Wahid H.
AU - Ali, Abdullah
AU - Chitnis, Nakul
N1 - Funding Information: We would like to thank Kim Lindblade, Lars Kamber, Aurélien Cavelan, Clara Champagne, Emma Fairbanks, Thiery Masserey and Pascal Grobecker for their helpful discussions and feedback on the manuscript. We would like to thank Faiza Abbas for her support of this project. Calculations were performed at the sciCORE ( http://scicore.unibas.ch/ ) scientific computing center at University of Basel. A.M.D. and N.C. were supported by the Bill and Melinda Gates Foundation (INV025569). Funding for the RADZEC study was provided by the Swiss Tropical and Public Health Institute and the US President’s Malaria Initiative via the US Agency for International Development/Tanzania under the terms of an inter-agency agreement with Centers for Disease Control and Prevention (CDC) and the US Agency for International Development/Tanzania through a cooperative agreement with the MEASURE Evaluation consortium, under the associate cooperative agreement No. AID-621-LA-14-00001 titled ’Measure Phase III-Strengthening the monitoring, evaluation and research capacity of the community health and social service programmes in the United Republic of Tanzania’. This grant supported the initial data collection and analysis conducted by M.W.H., J.O.Y., L.S. and B.S.F. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the President’s Malaria Initiative via the US Agency for International Development, or other employing organizations or sources of funding. BSF was additionally supported by a PhD scholarship from the Canton of Basel-Stadt, Switzerland. Funding Information: We would like to thank Kim Lindblade, Lars Kamber, Aurélien Cavelan, Clara Champagne, Emma Fairbanks, Thiery Masserey and Pascal Grobecker for their helpful discussions and feedback on the manuscript. We would like to thank Faiza Abbas for her support of this project. Calculations were performed at the sciCORE (http://scicore.unibas.ch/) scientific computing center at University of Basel. A.M.D. and N.C. were supported by the Bill and Melinda Gates Foundation (INV025569). Funding for the RADZEC study was provided by the Swiss Tropical and Public Health Institute and the US President’s Malaria Initiative via the US Agency for International Development/Tanzania under the terms of an inter-agency agreement with Centers for Disease Control and Prevention (CDC) and the US Agency for International Development/Tanzania through a cooperative agreement with the MEASURE Evaluation consortium, under the associate cooperative agreement No. AID-621-LA-14-00001 titled ’Measure Phase III-Strengthening the monitoring, evaluation and research capacity of the community health and social service programmes in the United Republic of Tanzania’. This grant supported the initial data collection and analysis conducted by M.W.H., J.O.Y., L.S. and B.S.F. The opinions expressed herein are those of the authors and do not necessarily reflect the views of the President’s Malaria Initiative via the US Agency for International Development, or other employing organizations or sources of funding. BSF was additionally supported by a PhD scholarship from the Canton of Basel-Stadt, Switzerland. Publisher Copyright: © 2023, The Author(s).
PY - 2023/12
Y1 - 2023/12
N2 - Malaria cases can be classified as imported, introduced or indigenous cases. The World Health Organization's definition of malaria elimination requires an area to demonstrate that no new indigenous cases have occurred in the last three years. Here, we present a stochastic metapopulation model of malaria transmission that distinguishes between imported, introduced and indigenous cases, and can be used to test the impact of new interventions in a setting with low transmission and ongoing case importation. We use human movement and malaria prevalence data from Zanzibar, Tanzania, to parameterise the model. We test increasing the coverage of interventions such as reactive case detection; implementing new interventions including reactive drug administration and treatment of infected travellers; and consider the potential impact of a reduction in transmission on Zanzibar and mainland Tanzania. We find that the majority of new cases on both major islands of Zanzibar are indigenous cases, despite high case importation rates. Combinations of interventions that increase the number of infections treated through reactive case detection or reactive drug administration can lead to substantial decreases in malaria incidence, but for elimination within the next 40 years, transmission reduction in both Zanzibar and mainland Tanzania is necessary.
AB - Malaria cases can be classified as imported, introduced or indigenous cases. The World Health Organization's definition of malaria elimination requires an area to demonstrate that no new indigenous cases have occurred in the last three years. Here, we present a stochastic metapopulation model of malaria transmission that distinguishes between imported, introduced and indigenous cases, and can be used to test the impact of new interventions in a setting with low transmission and ongoing case importation. We use human movement and malaria prevalence data from Zanzibar, Tanzania, to parameterise the model. We test increasing the coverage of interventions such as reactive case detection; implementing new interventions including reactive drug administration and treatment of infected travellers; and consider the potential impact of a reduction in transmission on Zanzibar and mainland Tanzania. We find that the majority of new cases on both major islands of Zanzibar are indigenous cases, despite high case importation rates. Combinations of interventions that increase the number of infections treated through reactive case detection or reactive drug administration can lead to substantial decreases in malaria incidence, but for elimination within the next 40 years, transmission reduction in both Zanzibar and mainland Tanzania is necessary.
UR - http://www.scopus.com/inward/record.url?scp=85159738760&partnerID=8YFLogxK
U2 - https://doi.org/10.1038/s41467-023-38379-8
DO - https://doi.org/10.1038/s41467-023-38379-8
M3 - Article
C2 - 37173317
SN - 2041-1723
VL - 14
JO - Nature communications
JF - Nature communications
IS - 1
M1 - 2750
ER -