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@#Newer diagnostic tests for COVI D-19 such as antigen tests are being used for rapid identification of cases. Compared to reverse transcriptase polymerase chain reaction (RT-PCR), these tests offer simpler collection and processing. This study aims to determine the accuracy of a SARS-CoV-2 antigen-detecting rapid diagnostic test (Ag-ROT) using saliva compared to nasopharyngeal and oropharyngeal swab (NPS/OPS) RT- PCR among patients tested in the Emergency Room at Makati Medical Center. Patients who underwent NPS/OPS RT-PCR and who consented to participate in the study were asked to submit salivary sample to be analyzed using the Standard™ Q Covid-19 Ag Saliva Test kit. A total of 366 samples were collected . The overall accuracy was 81 .69% with a sensitivity of 63.58% and a specificity of 97.93%. Subgroup analyses as to processing time, number of days from symptom onset, and presence or absence of symptoms had no effect the overall accuracy. The Standard™ Q Covid-19 Ag Saliva Test kit was able to satisfy the ~97% specificity recommended by the WHO for SARS-CoV-2 Ag-RDTs but did not meet the minimum performance requirements of ~80% sensitivity. A positive test results can help in the initiation of early treatment and isolation of cases, but a negative test should still be confirmed by NPS/OPS RT-PCR test.
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Introduction:Geographical Information System (GIS) has proven to be very useful for large scale mapping of ecosystems, land use and cover, disease prevalence, risk mapping and forecasting. GIS establish relationship or link between vector borne diseases and associated environmental factors thereby providing explanation for spatial distribution pattern, possible causes of diseases outbreak andimplications on the community.Aims and Objectives:Our approach in this study was to define and identify areas and places that are exposed to Malaria risk through proximity analysis and to compare geospatial risk with laboratory diagnosed malaria epidemiology. Methodology:Garmin GPS was used to capture the geographic coordinates of six (6) selected settlements and overlaid with georeferenced and processed satellite images in the study area. GIS modeling was performed on risk factors using weighted overlay technique to produce malaria risk map. A total of One hundred and thirty-five (135) vulnerable individuals were diagnosed for Malaria with light Olympus microscope and rapid diagnostic kit (RDT). Data were entered and analyzed using R-Package for Statistical Computing and Graphics.Results:Proximity to malaria risk follows relatively the order Apodu > Central Malete > Elemere > KWASU Campus > Gbugudu. Apodu being the largest place with proximity to malaria risk, within 500m radius. The risk index increases as one move away from the center of the settlement. The possible explanation for this high risk could be the presence of pond / lake in Apodu. This is a good breeding site for mosquito couple with dense vegetation as one move away from the centre of the settlements. Unlike Apodu, Gbugudu was at medium risk at 100m buffer (60%) but the risk index decreases as one move away from the settlement centre. The absence of thick vegetation and presence of numerous open farms and partly cultivated farmlands on the eastern part could have been responsible for reduction in risk index. Dense vegetation and ponds were observed within Apodu, while Central Malete was built up with dense vegetation are possible reasons for the high-risk index, while settlements within 1 km radius around KWASU campus recorded lower risk index possibly dueto low vegetation. The geospatial malaria risk analysis correlates with the laboratory-based test results. RDT kits and light microscopy results showed Apodu having the highest malaria prevalence with 46% and 58.7% followed by Elemere 41% and 30.3% respectively. When calculating prevalence by aggregating results across all communities, Apodu still had the highest malaria prevalence for the whole region. RDT and light microscopy results combined for all communities had Apodu with malaria prevalence of 21.48% and 27.4% followed by Elemere with 11.85% and 12.5% respectively. Gbugudu had the least malaria prevalence within the region with 3.7% and 7.4% respectively.Discussion and Conclusion:Findings of this study showed dense vegetation and ponds within Apodu, Elemere and Central Malete served as good breeding site for mosquitoes and were responsible for the high-risk index at these areas. Settlements within 1 km radius around KWASU campus recorded lower index possibly due to low vegetation. Results from this study indicate that the degree of malaria parasitaemia in the three major settlements correlates directly with the remote sensing data
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Objective To evaluate the effectiveness of the application of Wondfo Rapid Diagnostic Kit (RDTs) in the diagnosis of imported malaria cases in the Malaria Reference Laboratory of Hubei Provence. Methods The complete blood samples of malaria cases and negative card deletion cases reported in Hubei Province from January 2015 to June 2018 were collected and retrospectively analyzed. The results of the provincial malaria reference laboratory were used as the standard, and were compared with those results detected by RDTs, microscopic examination and nested PCR. The differences were statistically analyzed. Results A total of 440 complete samples were collected by the Malaria Reference Laboratory of Hubei Provence, of which 418 samples were confirmed as positive, and 22 samples were confirmed as negative. In terms of the identification ability of P. falciparum, RDTs performed the best, with a coincidence rate of 100.00%, and the coincidence rates nested PCR and microscopic examination were 97.49% and 91.40%, respectively. In terms of the identification specificity for another 3 species of Plasmodium (P. vivax, P. ovarian and P. vivax), nested PCR was the best, the microscopy method was the second best, and RDTs was the lowest. Based on the comprehensive analysis of 12 individual indicators, RDTs had the highest score (32), while the microscopic examination and nested PCR scored 24 and 19, respectively. Conclusion RDTs had certain advantages in the detection of malaria, but they had a low identification specificity for different species. Thus, they can be used as auxiliary tools for microscopic examination and widely used in surveillance work after malaria elimination in Hubei Province.