000256253 001__ 256253
000256253 005__ 20190702160328.0
000256253 0247_ $$2doi$$a10.1371/journal.pmed.1002509
000256253 037__ $$aARTICLE
000256253 245__ $$aThe potential impact of case-area targeted interventions in response to cholera outbreaks: A modeling study
000256253 260__ $$c2018-02-28
000256253 269__ $$a2018-02-28
000256253 336__ $$aJournal Articles
000256253 520__ $$aBackground Cholera prevention and control interventions targeted to neighbors of cholera cases (case-area targeted interventions [CATIs]), including improved water, sanitation, and hygiene, oral cholera vaccine (OCV), and prophylactic antibiotics, may be able to efficiently avert cholera cases and deaths while saving scarce resources during epidemics. Efforts to quickly target interventions to neighbors of cases have been made in recent outbreaks, but little empirical evidence related to the effectiveness, efficiency, or ideal design of this approach exists. Here, we aim to provide practical guidance on how CATIs might be used by exploring key determinants of intervention impact, including the mix of interventions, “ring” size, and timing, in simulated cholera epidemics fit to data from an urban cholera epidemic in Africa. Methods and findings We developed a micro-simulation model and calibrated it to both the epidemic curve and the small-scale spatiotemporal clustering pattern of case households from a large 2011 cholera outbreak in N’Djamena, Chad (4,352 reported cases over 232 days), and explored the potential impact of CATIs in simulated epidemics. CATIs were implemented with realistic logistical delays after cases presented for care using different combinations of prophylactic antibiotics, OCV, and/or point-of-use water treatment (POUWT) starting at different points during the epidemics and targeting rings of various radii around incident case households. Our findings suggest that CATIs shorten the duration of epidemics and are more resource-efficient than mass campaigns. OCV was predicted to be the most effective single intervention, followed by POUWT and antibiotics. CATIs with OCV started early in an epidemic focusing on a 100-m radius around case households were estimated to shorten epidemics by 68% (IQR 62% to 72%), with an 81% (IQR 69% to 87%) reduction in cases compared to uncontrolled epidemics. These same targeted interventions with OCV led to a 44-fold (IQR 27 to 78) reduction in the number of people needed to target to avert a single case of cholera, compared to mass campaigns in high-cholera-risk neighborhoods. The optimal radius to target around incident case households differed by intervention type, with antibiotics having an optimal radius of 30 m to 45 m compared to 70 m to 100 m for OCV and POUWT. Adding POUWT or antibiotics to OCV provided only marginal impact and efficiency improvements. Starting CATIs early in an epidemic with OCV and POUWT targeting those within 100 m of an incident case household reduced epidemic durations by 70% (IQR 65% to 75%) and the number of cases by 82% (IQR 71% to 88%) compared to uncontrolled epidemics. CATIs used late in epidemics, even after the peak, were estimated to avert relatively few cases but substantially reduced the number of epidemic days (e.g., by 28% [IQR 15% to 45%] for OCV in a 100-m radius). While this study is based on a rigorous, data-driven approach, the relatively high uncertainty about the ways in which POUWT and antibiotic interventions reduce cholera risk, as well as the heterogeneity in outbreak dynamics from place to place, limits the precision and generalizability of our quantitative estimates. Conclusions In this study, we found that CATIs using OCV, antibiotics, and water treatment interventions at an appropriate radius around cases could be an effective and efficient way to fight cholera epidemics. They can provide a complementary and efficient approach to mass intervention campaigns and may prove particularly useful during the initial phase of an outbreak, when there are few cases and few available resources, or in order to shorten the often protracted tails of cholera epidemics.
000256253 700__ $$aFinger, Flavio
000256253 700__ $$g182988$$0240021$$aBertuzzo, Enrico
000256253 700__ $$aLuquero, Francisco J.
000256253 700__ $$aNaibei, Nathan
000256253 700__ $$aTouré, Brahima
000256253 700__ $$aAllan, Maya
000256253 700__ $$aPorten, Klaudia
000256253 700__ $$aLessler, Justin
000256253 700__ $$aRinaldo, Andrea
000256253 700__ $$aAzman, Andrew S.
000256253 773__ $$tPLOS Medicine$$j15$$k2$$qe1002509
000256253 8560_ $$fandrea.rinaldo@epfl.ch
000256253 909C0 $$manna.rothenbuehler@epfl.ch$$mandrea.rinaldo@epfl.ch$$0252014$$zCharbonnier, Valérie$$xU10273$$pECHO
000256253 909CO $$particle$$pENAC$$ooai:infoscience.epfl.ch:256253
000256253 960__ $$abernard.sperandio@epfl.ch
000256253 961__ $$anoemi.cobolet@epfl.ch
000256253 973__ $$aEPFL$$sPUBLISHED$$rREVIEWED
000256253 980__ $$aARTICLE
000256253 981__ $$aoverwrite
000256253 981__ $$a253234