Impact of 1,7-malaria reactive community-based testing and response (1,7-mRCTR) approach on malaria prevalence in Tanzania.

BACKGROUND: Progress in malaria control has stalled in recent years and innovative surveillance and response approaches are needed to accelerate malaria control and elimination efforts in endemic areas of Africa. Building on a previous China-UK-Tanzania pilot study on malaria control, this study aimed to assess the impact of the 1,7-malaria Reactive Community-Based Testing and Response (1,7-mRCTR) approach implemented over two years in three districts of Tanzania. METHODS: The 1,7-mRCTR approach provides community-based malaria testing via rapid diagnostic tests and treatment in villages with the highest burden of malaria incidence based on surveillance data from health facilities. We used a difference-in-differences quasi-experimental design with linear probability models and two waves of cross-sectional household surveys to assess the impact of 1,7-mRCTR on malaria prevalence. We conducted sensitivity analyses to assess the robustness of our results, examined how intervention effects varied in subgroups, and explored alternative explanations for the observed results. RESULTS: Between October 2019 and September 2021, 244,771 community-based malaria rapid tests were completed in intervention areas, and each intervention village received an average of 3.85 rounds of 1-7mRCTR. Malaria prevalence declined from 27.4% at baseline to 11.7% at endline in the intervention areas and from 26.0% to 16.0% in the control areas. 1,7-mRCTR was associated with a 4.5-percentage-point decrease in malaria prevalence (95% confidence interval: - 0.067, - 0.023), equivalent to a 17% reduction from the baseline. In Rufiji, a district characterized by lower prevalence and where larviciding was additionally provided, 1,7-mRCTR was associated with a 63.9% decline in malaria prevalence. CONCLUSIONS: The 1,7-mRCTR approach reduced malaria prevalence. Despite implementation interruptions due to the COVID-19 pandemic and supply chain challenges, the study provided novel evidence on the effectiveness of community-based reactive approaches in moderate- to high-endemicity areas and demonstrated the potential of South-South cooperation in tackling global health challenges.

Accelerated Fatigue Model for Predicting Composite Restoration Failure.

An empirical method is proposed to predict the clinical performance of resin composite dental restorations by using laboratory data derived from simple specimens subjected to chemical degradation and accelerated cyclic fatigue. Three resin composites were used to fill dentin disks (2-mm inner diameter, 5-mm outer diameter, and 2 mm thick) made from bovine incisor roots. The specimens (n = 30 per group) were aged with different durations of a low-pH challenge (0, 24, and 48 h under pH 4.5) before being subjected to diametral compression with either a monotonically increasing load (fast fracture) or a cyclic load with a continuously increasing amplitude (accelerated fatigue). The data from 1 material were used to establish the relationship between laboratory time (number of cycles) and clinical time to failure (years) via the respective survival probability curves. The temporal relationship was then used to predict the clinical rates of failure for restorations made of the other 2 materials, and the predictions were compared with the clinical data to assess their accuracy. Although there were significant differences in the fast fracture strength among the groups of materials or durations of chemical challenge, fatigue testing was much better at separating the groups. Linear relationships were found between the laboratory and clinical times to failure for the first material (R2 = 0.90, 0.90, and 0.62 for the 0-, 24-, and 48-h low-pH groups, respectively). The clinical life of restorations made of the other 2 materials was best predicted with data from the 48-h low-pH groups. In conclusion, an accelerated fatigue model was successfully calibrated and applied to predict the clinical failure of resin composite restorations, and the predictions based on data obtained from chemically aged specimens provided the best agreement with clinical data.

A Review of Mechano-Biochemical Models for Testing Composite Restorations.

Due to the severe mechano-biochemical conditions in the oral cavity, many dental restorations will degrade and eventually fail. For teeth restored with resin composite, the major modes of failure are secondary caries and fracture of the tooth or restoration. While clinical studies can answer some of the more practical questions, such as the rate of failure, fundamental understanding on the failure mechanism can be obtained from laboratory studies using simplified models more effectively. Reviewed in this article are the 4 main types of models used to study the degradation of resin-composite restorations, namely, animal, human in vivo or in situ, in vitro biofilm, and in vitro chemical models. The characteristics, advantages, and disadvantages of these models are discussed and compared. The tooth-restoration interface is widely considered the weakest link in a resin composite restoration. To account for the different types of degradation that can occur (i.e., demineralization, resin hydrolysis, and collagen degradation), enzymes such as esterase and collagenase found in the oral environment are used, in addition to acids, to form biochemical models to test resin-composite restorations in conjunction with mechanical loading. Furthermore, laboratory tests are usually performed in an accelerated manner to save time. It is argued that, for an accelerated multicomponent model to be representative and predictive in terms of both the mode and the speed of degradation, the individual components must be synchronized in their rates of action and be calibrated with clinical data. The process of calibrating the in vitro models against clinical data is briefly described. To achieve representative and predictive in vitro models, more comparative studies of in vivo and in vitro models are required to calibrate the laboratory studies.