TY - JOUR
T1 - An immune system for the city
T2 - A cluster-randomized trial of a new paradigm for surveillance and control of disease vectors
AU - Levy, Michael Z.
AU - Tamayo, Laura D.
AU - Condori-Pino, Carlos E.
AU - Arevalo-Nieto, Claudia
AU - Castillo-Neyra, Ricardo
AU - Paz-Soldán, Valerie A.
N1 - Publisher Copyright:
Copyright: © 2026 Levy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. http://creativecommons.org/licenses/by/4.0/
PY - 2026
Y1 - 2026
N2 - Vector-borne pathogens continue to emerge, kill and harm humans with unrelenting regularity. Conventional strategies for controlling insect vectors grew out of the military; communication is hierarchical, responses unilateral, and regulation predetermined. We developed an alternative approach, modeled after the adaptive immune system, and compared the approaches through a cluster-randomized trial in the context of an ongoing urban Chagas disease vector control campaign in Arequipa, Peru. Clusters consisted of pre-defined geographic jurisdictions of health facilities, and averaged 2,271 households. Thirty clusters were assigned to the immune arm, and thirty to the conventional arm, balancing on antecedents related to the probability of vector infestation. Following delays, the trial initiated in October 2021. We report here early results from a pre-planned interim analysis scheduled for March 2023. In the immune arm 23 infested households were discovered and confirmed in 10 separate foci; in the conventional arm only 5 infested households were discovered and confirmed, and all were from the same focus. The immune approach was adaptive, and more effort was expended upon confirmation of an infestation (1085.2 person days in the immune arm vs 864.2 in the conventional; Rate ratio 23/1085.2:5/864.2 = 3.66 [1.49 - 10.60], p-value = 0.0038). Vector surveillance approaches modeled after the immune system are a potentially more effective alternative to conventional approaches, especially to control vector borne diseases in cities and other complex environments.
AB - Vector-borne pathogens continue to emerge, kill and harm humans with unrelenting regularity. Conventional strategies for controlling insect vectors grew out of the military; communication is hierarchical, responses unilateral, and regulation predetermined. We developed an alternative approach, modeled after the adaptive immune system, and compared the approaches through a cluster-randomized trial in the context of an ongoing urban Chagas disease vector control campaign in Arequipa, Peru. Clusters consisted of pre-defined geographic jurisdictions of health facilities, and averaged 2,271 households. Thirty clusters were assigned to the immune arm, and thirty to the conventional arm, balancing on antecedents related to the probability of vector infestation. Following delays, the trial initiated in October 2021. We report here early results from a pre-planned interim analysis scheduled for March 2023. In the immune arm 23 infested households were discovered and confirmed in 10 separate foci; in the conventional arm only 5 infested households were discovered and confirmed, and all were from the same focus. The immune approach was adaptive, and more effort was expended upon confirmation of an infestation (1085.2 person days in the immune arm vs 864.2 in the conventional; Rate ratio 23/1085.2:5/864.2 = 3.66 [1.49 - 10.60], p-value = 0.0038). Vector surveillance approaches modeled after the immune system are a potentially more effective alternative to conventional approaches, especially to control vector borne diseases in cities and other complex environments.
UR - https://www.scopus.com/pages/publications/105044468469
U2 - 10.1371/journal.pntd.0014464
DO - 10.1371/journal.pntd.0014464
M3 - Artículo
C2 - 42330036
AN - SCOPUS:105044468469
SN - 1935-2727
VL - 20
JO - PLoS Neglected Tropical Diseases
JF - PLoS Neglected Tropical Diseases
IS - 6
M1 - e0014464
ER -