RESUMO
The African region was predicted to have worse COVID-19 infection and death rates due to challenging health systems and social determinants of health. However, in the 10 months after its first case, Rwanda recorded 10316 cases and 133 COVID-19-related deaths translating to a case fatality rate (CFR) of 1.3%, which raised the question: why does Rwanda have a low COVID-19 CFR? Here we analysed COVID-19 data and explored possible explanations to better understand the disease burden in the context of Rwanda's infection control strategies.We investigated whether the age distribution plays a role in the observed low CFR in Rwanda by comparing the expected number of deaths for 10-year age bands based on the CFR reported in other countries with the observed number of deaths for each age group. We found that the age-specific CFRs in Rwanda are similar to or, in some older age groups, slightly higher than those in other countries, suggesting that the lower population level CFR reflects the younger age structure in Rwanda, rather than a lower risk of death conditional on age. We also accounted for Rwanda's comprehensive SARS-CoV-2 testing strategies and reliable documentation of COVID-19-related deaths and deduced that these measures may have allowed them to likely identify more asymptomatic or mild cases than other countries and reduced their reported CFR.Overall, the observed low COVID-19 deaths in Rwanda is likely influenced by the combination of effective infection control strategies, reliable identification of cases and reporting of deaths, and the population's young age structure.
Assuntos
COVID-19/mortalidade , Mortalidade/tendências , Adolescente , Adulto , Distribuição por Idade , Idoso , Idoso de 80 Anos ou mais , Teste para COVID-19 , Criança , Pré-Escolar , Controle de Doenças Transmissíveis/métodos , Feminino , Humanos , Lactente , Masculino , Pessoa de Meia-Idade , Ruanda/epidemiologia , SARS-CoV-2/isolamento & purificação , Adulto JovemRESUMO
A 36-year-old male patient was diagnosed with tuberculosis in Antwerp, Belgium, in May 2018. His lymph node aspirate initially tested rifampicin resistant in Xpert MTB/RIF Ultra, but tested susceptible in all other tests including targeted deep sequencing due to a rare matrix effect in the Xpert MTB/RIF Ultra reaction tube.
RESUMO
BACKGROUND: Mycobacterium tuberculosis rapid diagnostic tests (RDTs) are widely employed in routine laboratories and national surveys for detection of rifampicin-resistant (RR)-TB. However, as next-generation sequencing technologies have become more commonplace in research and surveillance programs, RDTs are being increasingly complemented by whole genome sequencing (WGS). While comparison between RDTs is difficult, all RDT results can be derived from WGS data. This can facilitate continuous analysis of RR-TB burden regardless of the data generation technology employed. By converting WGS to RDT results, we enable comparison of data with different formats and sources particularly for low- and middle-income high TB-burden countries that employ different diagnostic algorithms for drug resistance surveys. This allows national TB control programs (NTPs) and epidemiologists to utilize all available data in the setting for improved RR-TB surveillance. METHODS: We developed the Python-based MycTB Genome to Test (MTBGT) tool that transforms WGS-derived data into laboratory-validated results of the primary RDTs-Xpert MTB/RIF, XpertMTB/RIF Ultra, GenoType MDRTBplus v2.0, and GenoscholarNTM+MDRTB II. The tool was validated through RDT results of RR-TB strains with diverse resistance patterns and geographic origins and applied on routine-derived WGS data. RESULTS: The MTBGT tool correctly transformed the single nucleotide polymorphism (SNP) data into the RDT results and generated tabulated frequencies of the RDT probes as well as rifampicin-susceptible cases. The tool supplemented the RDT probe reactions output with the RR-conferring mutation based on identified SNPs. The MTBGT tool facilitated continuous analysis of RR-TB and Xpert probe reactions from different platforms and collection periods in Rwanda. CONCLUSION: Overall, the MTBGT tool allows low- and middle-income countries to make sense of the increasingly generated WGS in light of the readily available RDT results, and assess whether currently implemented RDTs adequately detect RR-TB in their setting. With its feature to transform WGS to RDT results and facilitate continuous RR-TB data analysis, the MTBGT tool may bridge the gap between and among data from periodic surveys, continuous surveillance, research, and routine tests, and may be integrated within the national information system for use by the NTP and epidemiologists to improve setting-specific RR-TB control. The MTBGT source code and accompanying documentation are available at https://github.com/KamelaNg/MTBGT.
RESUMO
We compared the ability of commercial and non-commercial, phenotypic and genotypic rapid drug susceptibility tests (DSTs) to detect rifampicin resistance (RR)-conferring 'disputed' mutations frequently missed by Mycobacterium Growth Indicator Tube (MGIT), namely L430P, D435Y, L452P, and I491F. Strains with mutation S450L served as positive control while wild-types were used as negative control. Of the 38 mutant strains, 5.7% were classified as RR by MGIT, 16.2% by Trek Sensititre MYCOTB MIC plate, 19.4% by resazurin microtiter plate assay (REMA), 50.0% by nitrate reductase assay (NRA), and 62.2% by microscopic observation direct susceptibility testing (MODS). Reducing MGIT rifampicin concentration to 0.5 µg/ml, and/or increasing incubation time, enhanced detection of disputed mutations from 5.7% to at least 65.7%, particularly for mutation I491F (from 0.0 to 75.0%). Compared with MGIT at standard pre-set time with 0.25 µg/ml ECOFF as breakpoint, we found a statistically significant increase in the ability of MGIT to resolve disputed mutants and WT strains at extended incubation period of 15 and 21 days, with 0.5 µg/ml and 1 µg/ml ECOFF respectively. MODS detected 75.0% of the I491F strains and NRA 62.5%, while it was predictably missed by all molecular assays. Xpert MTB/RIF, Xpert Ultra, and GenoscholarTB-NTM + MDRTB detected all mutations within the 81 bp RR determining region. Only GenoType MTBDRplus version 2 missed mutation L430P in 2 of 11 strains. Phenotypic and genotypic DSTs varied greatly in detecting occult rifampicin resistance. None of these methods detected all disputed mutations without misclassifying wild-type strains.
Assuntos
Proteínas de Bactérias/genética , RNA Polimerases Dirigidas por DNA/genética , Farmacorresistência Bacteriana/genética , Mutação , Mycobacterium tuberculosis/genética , Rifampina/farmacologia , Antituberculosos , Proteínas de Bactérias/efeitos dos fármacos , RNA Polimerases Dirigidas por DNA/efeitos dos fármacos , Genes Bacterianos , Genótipo , Testes de Sensibilidade Microbiana , Mycobacterium tuberculosis/efeitos dos fármacosRESUMO
Rifampin heteroresistance-where rifampin-resistant and -susceptible tuberculosis (TB) bacilli coexist-may result in failed standard TB treatment and potential spread of rifampin-resistant strains. The detection of rifampin heteroresistance in routine rapid diagnostic tests (RDTs) allows for patients to receive prompt and effective multidrug-resistant-TB treatment and may improve rifampin-resistant TB control. The limit of detection (LOD) of rifampin heteroresistance for phenotypic drug susceptibility testing by the proportion method is 1% and, yet, is insufficiently documented for RDTs. We, therefore, aimed to determine, for the four RDTs (XpertMTB/RIF, XpertMTB/RIF Ultra, GenoTypeMTBDRplusv2.0, and GenoscholarNTM+MDRTBII), the LOD per probe and mutation, validated by CFU counting and targeted deep sequencing (Deeplex-MycTB). We selected one rifampin-susceptible and four rifampin-resistant strains, with mutations D435V, H445D, H445Y, and S450L, respectively, mixed them in various proportions in triplicate, tested them with each RDT, and determined the LODs per mutation type. Deeplex-MycTB revealed concordant proportions of the minority resistant variants in the mixtures. The Deeplex-MycTB-validated LODs ranged from 20% to 80% for XpertMTB/RIF, 20% to 70% for Xpert Ultra, 5% to 10% for GenoTypeMTBDRplusv2.0, and 1% to 10% for GenoscholarNTM+MDRTBII for the different mutations. Deeplex-MycTB, GenoTypeMTBDRplusv2.0, and GenoscholarNTM+MDRTBII provide explicit information on rifampin heteroresistance for the most frequently detected mutations. Classic Xpert and Ultra report rifampin heteroresistance as rifampin resistance, while Ultra may denote rifampin heteroresistance through "mixed patterns" of wild-type and mutant melt probe, melt peak temperatures. Overall, our findings inform end users that the threshold for reporting resistance in the case of rifampin heteroresistance is the highest for Classic Xpert and Ultra to resolve phenotypic and genotypic discordant rifampin-resistant TB results.