Evidence map›Paper›PMID 40376505›Full record

ArticleChina CDC weekly2025

Impact of Implementation Interruptions of 1,7-Malaria Reactive Community-Based Testing and Response Approach on Malaria Control Efforts - Southern Tanzania.

Yuejin Li, Jinxin Zheng, Yeromin P Mlacha, Shenning Lu, Salim Abdulla, Qin Li, Ge Yan, Xiaonong Zhou, Ning Xiao, Victoria Githu and 6 more

Abstract read
In one paragraph

Article in China CDC weekly, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Yuejin Li *Shandong Institute of Parasitic Diseases, Shandong First Medical University & Shandong Academy of Medical Sciences, Jining City, Shandong Province, China.
Jinxin Zheng *National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai, China.
Yeromin P Mlacha *Ifakara Health Institute, Environmental Health and Ecological Science, Dar es Salaam, United Republic of Tanzania.
Shenning LuNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai, China.
Salim AbdullaIfakara Health Institute, Environmental Health and Ecological Science, Dar es Salaam, United Republic of Tanzania.
Qin LiNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai, China.
Ge YanShandong Institute of Parasitic Diseases, Shandong First Medical University & Shandong Academy of Medical Sciences, Jining City, Shandong Province, China.
Xiaonong ZhouNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai, China.
Ning XiaoNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai, China.
Victoria GithuIfakara Health Institute, Environmental Health and Ecological Science, Dar es Salaam, United Republic of Tanzania.
Tegemeo GavanaIfakara Health Institute, Environmental Health and Ecological Science, Dar es Salaam, United Republic of Tanzania.
Prosper ChakiIfakara Health Institute, Environmental Health and Ecological Science, Dar es Salaam, United Republic of Tanzania.
Peng BiSchool of Public Health, The University of Adelaide, Adelaide, South Australia, Australia.
Yuan SuiStatistical Center for HIV/AIDS Research and Prevention (SCHARP), Fred Hutchinson Cancer Center, Seattle, WA, USA.
Yongbin WangShandong Institute of Parasitic Diseases, Shandong First Medical University & Shandong Academy of Medical Sciences, Jining City, Shandong Province, China.
Duoquan WangNational Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research); NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases; National Center for International Research on Tropical Diseases, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Surveys from the China-Tanzania Malaria Control Project demonstrated that the 1,7-malaria Reactive Community-Based Testing and Response (1,7-mRCTR) approach significantly reduced malaria incidence rates. However, implementation was disrupted by security concerns, infectious disease outbreaks, and supply shortages. This study evaluates how these interruptions affected intervention effectiveness to inform future malaria control strategies. Methods: The study employed a two-phased design: Phase I (2016-2018) and Phase II (2019-2021). Weekly malaria incidence rates per 100 people were calculated from cases reported by local health facilities in the intervention areas during both phases. Seasonal and trend decomposition using loess (STL) and interrupted time series modeling with piecewise linear regression were used to evaluate the impact of disruptions on 1,7-mRCTR implementation effectiveness. Results: In Tanzania's 1,7-mRCTR areas, malaria incidence peaked during November-December and June-July. Phase I's 8-month interruption reversed the weekly trend from a 0.17% decline to a 0.58% increase ( Conclusions: This research demonstrates that Tanzania's malaria incidence is closely linked to seasonal patterns and consistent intervention efforts. Phase I's 8-month security-related interruption reduced 1,7-mRCTR effectiveness by 12.5%, while Phase II's 3-month pandemic-induced interruption caused only short-term fluctuations with minimal long-term impact. Rapid resumption of interventions after disruptions allowed for prompt recovery, highlighting the importance of adaptive strategies to maintain progress toward malaria control goals.

Indexed as

17-mRCTRImplementationInterrupted time series analysisMalariaSurveillance and response

Identifiers

PMID40376505
PMCPMC12075446

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.