Persistent, neuropathic-like trigeminal pain after dental implant loading

Painful post-traumatic trigeminal neuropathy (PTTN) is a known complication of dental implant therapy. Besides cases resulting of nerve damage during surgery or implant placement, some patients report delayed neuropathic-like symptoms only after implant

The role of health insurance in the coverage of oral health care in Senegal

Oral diseases costs are among the most expensive health care benefits. In Senegal, households contribute up to 37.6% of the national health spending through direct payments. The aim of this work was to study the role of health insurance in the coverage of oral health care in Senegal. The study was based on health insurance agents and policyholders. The study reveals that oral health care coverage through health insurance still does not meet requirements for treatment of oral infections. In financial terms, oral health care costs health insurance too much. As a result, carriers cover them partially. On top of that, the majority of the population’s lack of knowledge about mutual, because they have a little background on oral health care, the latter weighs heavily on health insurance leading to the use of self-medication, traditional medicine and handicraft prosthetists. The analysis reveals an unequal access to oral health care through the health insurance system. To bring under control the expenditure for oral health care, carriers and dental surgeons must work together to raise the populations’ awareness on community solidarity

Provider and User Acceptability of Integrated Treatment for the Control of Malaria and Helminths in Saraya, South-Eastern Senegal.

Integration of vertical programs for the control of malaria, schistosomiasis, and soil-transmitted helminthiasis has been recommended to achieve elimination of malaria and neglected tropical diseases (NTD) by 2030. This qualitative study was conducted within the context of a randomized controlled trial to explore the perceptions and views of parents/caregivers of at-risk children and healthcare providers to determine their acceptability of the integrated malaria-helminth treatment approach. Randomly selected parents/caregivers of children enrolled in the trial, healthcare providers, trial staff, malaria, and NTD program managers were interviewed using purpose-designed topic guides. Transcripts obtained from the interviews were coded and common themes identified using content analysis were triangulated. Fifty-seven study participants comprising 26 parents/caregivers, 10 study children aged ≥ 10 years, 15 trial staff, four healthcare providers, and two managers from the Senegal Ministry of Health were interviewed. Thirty-eight of the participants (66.7%) were males, and their ages ranged from 10 to 65 years. Overall, the integrated malaria-helminth treatment approach was considered acceptable, but the study participants expressed concerns about the taste, smell, and side effects associated with amodiaquine and praziquantel in the combination package. Reluctance to accept the medications was also observed among children aged 10 to 14 years due to peer influence and gender-sensitive cultural beliefs. Addressing concerns about the taste and smell of amodiaquine and praziquantel is needed to optimize the uptake of the integrated treatment program. Also, culturally appropriate strategies need to be put in place to cater for the inclusion of children aged 10 to 14 years in this approach

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Exploring the Methodological Approaches of Studies on Radiographic Databases Used in Cariology to Feed Artificial Intelligence: A Systematic Review

International audienceIntroduction: A growing number of studies on diagnostic imaging show superior efficiency and accuracy of computer-aided diagnostic systems compared to those of certified dentists. This methodological systematic review aimed to evaluate the different methodological approaches used by studies focusing on machine learning and deep learning that have used radiographic databases to classify, detect, and segment dental caries. Methods: The protocol was registered in PROSPERO before data collection (CRD42022348097). Literature research was performed in MEDLINE, Embase, IEEE Xplore, and Web of Science until December 2022, without language restrictions. Studies and surveys using a dental radiographic database for the classification, detection, or segmentation of carious lesions were sought. Records deemed eligible were retrieved and further assessed for inclusion by two reviewers who resolved any discrepancies through consensus. A third reviewer was consulted when any disagreements or discrepancies persisted between the two reviewers. After data extraction, the same reviewers assessed the methodological quality using the CLAIM and QUADAS-AI checklists. Results: After screening 325 articles, 35 studies were eligible and included. The bitewing was the most commonly used radiograph (n = 17) at the time when detection (n = 15) was the most explored computer vision task. The sample sizes used ranged from 95 to 38,437, while the augmented training set ranged from 300 to 315,786. Convolutional neural network was the most commonly used model. The mean completeness of CLAIM items was 49% (SD ± 34%). The applicability of the CLAIM checklist items revealed several weaknesses in the methodology of the selected studies: most of the studies were monocentric, and only 9% of them used an external test set when evaluating the model’s performance. The QUADAS-AI tool revealed that only 43% of the studies included in this systematic review were at low risk of bias concerning the standard reference domain. Conclusion: This review demonstrates that the overall scientific quality of studies conducted to feed artificial intelligence algorithms is low. Some improvement in the design and validation of studies can be made with the development of a standardized guideline for the reproducibility and generalizability of results and, thus, their clinical applications

Climate variability and malaria over West Africa

Malaria is a major public health problem in West Africa. Previous studies have shown that climate variability significantly affects malaria transmission. The lack of continuous observed weather station data and the absence of surveillance data for malaria over long periods have led to the use of reanalysis data to drive malaria models. In this study, we use the Liverpool Malaria Model (LMM) to simulate spatiotemporal variability of malaria in West Africa using daily rainfall and temperature from the following: Twentieth Century Reanalysis (20th CR), National Center for Environmental Prediction (NCEP), European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Reanalysis of the Twentieth Century (ERA20C), and interim ECMWF Re-Analysis (ERA-Interim). Malaria case data from the national surveillance program in Senegal are used for model validation between 2001 and 2016. The warm temperatures found over the Sahelian fringe of West Africa can lead to high malaria transmission during wet years. The rainfall season peaks in July to September over West Africa and Senegal, and the malaria season lasts from September to November, about 1-2 months after the rainfall peak. The long-term trends exhibit interannual and decadal variabilities. The LMM shows acceptable performance in simulating the spatial distribution of malaria incidence. However, some discrepancies are found. These results are useful for decision-makers who plan public health and control measures in affected West African countries. The study would have substantial implications for directing malaria surveillance activities and health policy. In addition, this malaria modeling framework could lead to the development of an early warning system for malaria in West Africa