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1.
JAMA Intern Med ; 2021 Apr 06.
Artigo em Inglês | MEDLINE | ID: mdl-33821922

RESUMO

Importance: Taiwan is one of the few countries with initial success in COVID-19 control without strict lockdown or school closure. The reasons remain to be fully elucidated. Objective: To compare and evaluate the effectiveness of case-based (including contact tracing and quarantine) and population-based (including social distancing and facial masking) interventions for COVID-19 in Taiwan. Design, Setting, and Participants: This comparative effectiveness study used a stochastic branching process model using COVID-19 epidemic data from Taiwan, an island nation of 23.6 million people, with no locally acquired cases of COVID-19 reported for 253 days between April and December 2020. Main Outcomes and Measures: Effective reproduction number of COVID-19 cases (the number of secondary cases generated by 1 primary case) and the probability of outbreak extinction (0 new cases within 20 generations). For model development and calibration, an estimation of the incubation period (interval from exposure to symptom onset), serial interval (time between symptom onset in an infector-infectee pair), and the statistical distribution of the number of any subsequent infections generated by 1 primary case was calculated. Results: This study analyzed data from 158 confirmed COVID-19 cases (median age, 45 years; interquartile range, 25-55 years; 84 men [53%]). An estimated 55% (95% credible interval [CrI], 41%-68%) of transmission events occurred during the presymptomatic stage. In our estimated analysis, case detection, contact tracing, and 14-day quarantine of close contacts (regardless of symptoms) was estimated to decrease the reproduction number from the counterfactual value of 2.50 to 1.53 (95% CrI, 1.50-1.57), which would not be sufficient for epidemic control, which requires a value of less than 1. In our estimated analysis, voluntary population-based interventions, if used alone, were estimated to have reduced the reproduction number to 1.30 (95% CrI, 1.03-1.58). Combined case-based and population-based interventions were estimated to reduce the reproduction number to below unity (0.85; 95% CrI, 0.78-0.89). Results were similar for additional analyses with influenza data and sensitivity analyses. Conclusions and Relevance: In this comparative effectiveness research study, the combination of case-based and population-based interventions (with wide adherence) may explain the success of COVID-19 control in Taiwan in 2020. Either category of interventions alone would have been insufficient, even in a country with an effective public health system and comprehensive contact tracing program. Mitigating the COVID-19 pandemic requires the collaborative effort of public health professionals and the general public.

2.
Lancet ; 397(10284): 1591-1596, 2021 Apr 24.
Artigo em Inglês | MEDLINE | ID: mdl-33838724

RESUMO

In the past decade, tuberculosis incidence has declined in much of the world, but has risen in central and South America. It is not yet clear what is driving this reversal of progress in tuberculosis control. Since 2000, the incarcerated population in central and South America has grown by 206%, the greatest increase in the world. Over the same period, notified tuberculosis cases among the incarcerated population (hereinafter termed persons deprived of their liberty [PDL], following the Inter-American Commission on Human Rights) have risen by 269%. In both central and South America, the rise of disease among PDL more than offsets tuberculosis control gains in the general population. Tuberculosis is increasingly concentrated among PDL; currently, 11% of all notified tuberculosis cases in central and South America occur among PDL who comprise less than 1% of the population. The extraordinarily high risk of acquiring tuberculosis within prisons creates a health and human rights crisis for PDL that also undermines wider tuberculosis control efforts. Controlling tuberculosis in this region will require countries to take urgent measures to prioritise the health of PDL.

3.
BMC Med ; 19(1): 95, 2021 Apr 20.
Artigo em Inglês | MEDLINE | ID: mdl-33874940

RESUMO

BACKGROUND: Large-scale rural-to-urban migration has changed the epidemiology of tuberculosis (TB) in large Chinese cities. We estimated the contribution of TB importation, reactivation of latent infection, and local transmission to new TB cases in Shanghai, and compared the potential impact of intervention options. METHODS: We developed a transmission dynamic model of TB for Songjiang District, Shanghai, which has experienced high migration over the past 25 years. We calibrated the model to local demographic data, TB notifications, and molecular epidemiologic studies. We estimated epidemiological drivers as well as future outcomes of current TB policies and compared this base-case scenario with scenarios describing additional targeted interventions focusing on migrants or vulnerable residents. RESULTS: The model captured key demographic and epidemiological features of TB among migrant and resident populations in Songjiang District, Shanghai. Between 2020 and 2035, we estimate that over 60% of TB cases will occur among migrants and that approximately 43% of these cases will result from recent infection. While TB incidence will decline under current policies, we estimate that additional interventions-including active screening and preventive treatment for migrants-could reduce TB incidence by an additional 20% by 2035. CONCLUSIONS: Migrant-focused TB interventions could produce meaningful health benefits for migrants, as well as for young residents who receive indirect protection as a result of reduced TB transmission in Shanghai. Further studies to measure cost-effectiveness are needed to evaluate the feasibility of these interventions in Shanghai and similar urban centers experiencing high migration volumes.

5.
Am J Epidemiol ; 2021 Apr 08.
Artigo em Inglês | MEDLINE | ID: mdl-33831148

RESUMO

Estimates of the reproductive number for novel pathogens such as severe acute respiratory syndrome coronavirus 2 are essential for understanding the potential trajectory of the epidemic and the level of intervention that is needed to bring the epidemic under control. However, most methods for estimating the basic reproductive number (R0) and time-varying effective reproductive number (Rt) assume that the fraction of cases detected and reported is constant through time. We explore the impact of secular changes in diagnostic testing and reporting on estimates of R0 and Rt using simulated data. We then compare these patterns to data on reported cases of coronavirus disease and testing practices from different states in the United States from March 4 to August 30, 2020. We find that changes in testing practices and delays in reporting can result in biased estimates of R0 and Rt. Examination of changes in the daily number of tests conducted and the percent of patients testing positive may be helpful for identifying the potential direction of bias. Changes in diagnostic testing and reporting processes should be monitored and taken into consideration when interpreting estimates of the reproductive number of coronavirus disease.

6.
Epidemics ; 35: 100443, 2021 Feb 20.
Artigo em Inglês | MEDLINE | ID: mdl-33676092

RESUMO

BACKGROUND: Evidence on local disease burden and the completeness of case detection represent important information for TB control programs. We present a new method for estimating subnational TB incidence and the fraction of individuals with incident TB who are diagnosed and treated in Brazil. METHODS: We compiled data on TB notifications and TB-related mortality in Brazil and specified an analytic model approximating incidence as the number of individuals exiting untreated active disease (sum of treatment initiation, death before treatment, and self-cure). We employed a Bayesian inference approach to synthesize data and adjust for known sources of bias. We estimated TB incidence and the fraction of cases treated, for each Brazilian state and the Federal District over 2008-2017. FINDINGS: For 2017, TB incidence was estimated as 41.5 (95 % interval: 40.7, 42.5) per 100 000 nationally, and ranged from 11.7-88.3 per 100 000 across states. The fraction of cases treated was estimated as 91.9 % (89.6 %, 93.7 %) nationally and ranged 86.0 %-94.8 % across states, with an estimated 6.9 (5.3, 9.2) thousand cases going untreated in 2017. Over 2008-2017, incidence declined at an average annual rate of 1.4 % (1.1 %, 1.9 %) nationally, and -1.1%-4.2 % across states. Over this period there was a 0.5 % (0.2 %, 0.9 %) average annual increase in the fraction of incident TB cases treated. INTERPRETATION: Time-series estimates of TB burden and the fraction of cases treated can be derived from routinely-collected data and used to understand variation in TB outcomes and trends.

7.
Lancet Public Health ; 6(5): e300-e308, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33765455

RESUMO

BACKGROUND: Prisons are recognised as high-risk environments for tuberculosis, but there has been little systematic investigation of the global and regional incidence and prevalence of tuberculosis, and its determinants, in prisons. We did a systematic review and meta-analysis to assess the incidence and prevalence of tuberculosis in incarcerated populations by geographical region. METHODS: In this systematic review and meta-analysis, we searched MEDLINE, Embase, Web of Knowledge, and the LILACS electronic database from Jan 1, 1980, to Nov 15, 2020, for cross-sectional and cohort studies reporting the incidence of Mycobacterium tuberculosis infection, incidence of tuberculosis, or prevalence of tuberculosis among incarcerated individuals in all geographical regions. We extracted data from individual studies, and calculated pooled estimates of incidence and prevalence through hierarchical Bayesian meta-regression modelling. We also did subgroup analyses by region. Incidence rate ratios between prisons and the general population were calculated by dividing the incidence of tuberculosis in prisons by WHO estimates of the national population-level incidence. FINDINGS: We identified 159 relevant studies; 11 investigated the incidence of M tuberculosis infection (n=16 318), 51 investigated the incidence of tuberculosis (n=1 858 323), and 106 investigated the prevalence of tuberculosis (n=6 727 513) in incarcerated populations. The overall pooled incidence of M tuberculosis infection among prisoners was 15·0 (95% credible interval [CrI] 3·8-41·6) per 100 person-years. The incidence of tuberculosis (per 100 000 person-years) among prisoners was highest in studies from the WHO African (2190 [95% CrI 810-4840] cases) and South-East Asia (1550 [240-5300] cases) regions and in South America (970 [460-1860] cases), and lowest in North America (30 [20-50] cases) and the WHO Eastern Mediterranean region (270 [50-880] cases). The prevalence of tuberculosis was greater than 1000 per 100 000 prisoners in all global regions except for North America and the Western Pacific, and highest in the WHO South-East Asia region (1810 [95% CrI 670-4000] cases per 100 000 prisoners). The incidence rate ratio between prisons and the general population was much higher in South America (26·9; 95% CrI 17·1-40·1) than in other regions, but was nevertheless higher than ten in the WHO African (12·6; 6·2-22·3), Eastern Mediterranean (15·6; 6·5-32·5), and South-East Asia (11·7; 4·1-27·1) regions. INTERPRETATION: Globally, people in prison are at high risk of contracting M tuberculosis infection and developing tuberculosis, with consistent disparities between prisons and the general population across regions. Tuberculosis control programmes should prioritise preventive interventions among incarcerated populations. FUNDING: US National Institutes of Health.


Assuntos
Saúde Global/estatística & dados numéricos , Prisioneiros/estatística & dados numéricos , Tuberculose/epidemiologia , Humanos , Incidência , Prevalência
8.
PLoS Comput Biol ; 17(2): e1008713, 2021 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-33556077

RESUMO

There is an emerging consensus that achieving global tuberculosis control targets will require more proactive case finding approaches than are currently used in high-incidence settings. Household contact tracing (HHCT), for which households of newly diagnosed cases are actively screened for additional infected individuals is a potentially efficient approach to finding new cases of tuberculosis, however randomized trials assessing the population-level effects of such interventions in settings with sustained community transmission have shown mixed results. One potential explanation for this is that household transmission is responsible for a variable proportion of population-level tuberculosis burden between settings. For example, transmission is more likely to occur in households in settings with a lower tuberculosis burden and where individuals mix preferentially in local areas, compared with settings with higher disease burden and more dispersed mixing. To better understand the relationship between endemic incidence levels, social mixing, and the impact of HHCT, we developed a spatially explicit model of coupled household and community transmission. We found that the impact of HHCT was robust across settings of varied incidence and community contact patterns. In contrast, we found that the effects of community contact tracing interventions were sensitive to community contact patterns. Our results suggest that the protective benefits of HHCT are robust and the benefits of this intervention are likely to be maintained across epidemiological settings.

9.
Emerg Infect Dis ; 27(3): 957-960, 2021 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-33622464

RESUMO

We adapted a mathematical modeling approach to estimate tuberculosis (TB) incidence and fraction treated for 101 municipalities of Brazil during 2008-2017. We found the average TB incidence rate decreased annually (0.95%), and fraction treated increased (0.30%). We estimated that 9% of persons with TB did not receive treatment in 2017.

10.
Med Decis Making ; 41(4): 386-392, 2021 05.
Artigo em Inglês | MEDLINE | ID: mdl-33504258

RESUMO

Policy makers need decision tools to determine when to use physical distancing interventions to maximize the control of COVID-19 while minimizing the economic and social costs of these interventions. We describe a pragmatic decision tool to characterize adaptive policies that combine real-time surveillance data with clear decision rules to guide when to trigger, continue, or stop physical distancing interventions during the current pandemic. In model-based experiments, we find that adaptive policies characterized by our proposed approach prevent more deaths and require a shorter overall duration of physical distancing than alternative physical distancing policies. Our proposed approach can readily be extended to more complex models and interventions.

11.
Clin Infect Dis ; 2021 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-33449999

RESUMO

BACKGROUND: Limitations in the sensitivity and accessibility of diagnostic tools for childhood tuberculosis contribute to the substantial gap between estimated cases and cases notified to national tuberculosis programs. Thus, tools to make accurate and rapid clinical diagnoses are necessary to initiate more children on antituberculosis treatment. METHODS: We analyzed data from a prospective cohort of children <13 years being routinely evaluated for pulmonary tuberculosis in Cape Town, South Africa from March 2012 to November 2017. We developed a regression model to describe the contributions of baseline clinical evaluation to the diagnosis of tuberculosis using standardized, retrospective case definitions. We included results from baseline chest radiography and Xpert MTB/RIF to the model to develop an algorithm with at least 90% sensitivity in predicting tuberculosis. RESULTS: Data from 478 children being evaluated for pulmonary tuberculosis were analyzed (median age: 16.2 months, interquartile range: 9.8-30.9); 242 (50.6%) were retrospectively classified with tuberculosis, of which 104 (43.0%) were bacteriologically-confirmed. The area under the receiver operating characteristic curve for the final model was 0.87. Clinical evidence identified 71.4% of all tuberculosis cases in this cohort, and inclusion of baseline chest radiography results increased the proportion to 89.3%. The algorithm was 90.1% sensitive and 52.1% specific, and maintained a sensitivity of above 90% among children <2 years or with low weight-for-age. CONCLUSIONS: Clinical evidence alone was sufficient to make most clinical antituberculosis treatment decisions. The use of evidence-based algorithms may improve decentralized, rapid treatment-initiation, reducing the global burden of childhood mortality.

12.
Epidemiology ; 32(1): 70-78, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-33009253

RESUMO

BACKGROUND: Risk of tuberculosis (TB) declines over time since Mycobacterium tuberculosis infection, but progression to clinical disease is still possible decades later. In the United States, most TB cases result from the progression of latent TB infection acquired over 2 years ago. METHODS: We synthesized evidence on TB natural history and incidence trends using a transmission-dynamic model. For the 2020 US population, we estimated average time since infection and annual, cumulative, and remaining lifetime risks of progression to TB, by nativity and age. RESULTS: For a newly infected adult with no other risk factors for progression to TB, estimated rates of progression declined from 38 (95% uncertainty interval: 33, 46) to 0.38 (0.32, 0.45) per 1000 person-years between the first and 25th year since infection. Cumulative risk over 25 years from new infection was 7.9% (7.0, 8.9). In 2020, an estimated average age of individuals with prevalent infection was 62 (61, 63) for the US-born population, 55 (54, 55) for non-US-born, and 57 (56, 58) overall. Average risks of developing TB over the remaining lifetime were 1.2% (1.0, 1.4) for US-born, 2.2% (1.8, 2.6) for non-US-born, and 1.9% (1.6, 2.2) for the general population. Risk estimates were higher for younger age groups. CONCLUSIONS: Our analysis suggests that, although newly infected individuals face appreciable lifetime TB risks, most US individuals with latent TB infection were infected long ago, and face low future risks of developing TB. Better approaches are needed for identifying recently infected individuals and those with elevated progression risks.

13.
Epidemics ; 33: 100419, 2020 Nov 10.
Artigo em Inglês | MEDLINE | ID: mdl-33242759

RESUMO

In the United States, new tuberculosis cases are increasingly concentrated within non-native-born populations. We estimated trends and differences in tuberculosis incidence rates for the non-U.S.-born population, at a resolution unobtainable from raw data. We obtained non-U.S.-born tuberculosis case reports for 2000-2016 from the National Tuberculosis Surveillance System, and population data from the American Community Survey and 2000 U.S. Census. We constructed generalized additive regression models to estimate incidence rates in terms of birth country, entry year, age at entry, and number of years since entry into the United States and described how these factors contribute to overall tuberculosis risk. Controlling for other factors, tuberculosis incidence rates were lower for more recent immigration cohorts, with an incidence risk ratio (IRR) of 10.2 (95 % confidence interval 7.0, 14.7) for the 1950 entry cohort compared to its 2016 counterpart. Greater years since entry and younger age at entry were associated with substantially lower incidence rates. IRRs for birth country varied between 8.86 (6.78, 11.52) for Somalia and 0.02 (0.01, 0.03) for Canada, compared to all non-U.S.-born residents in 2016. IRRs were positively correlated with WHO predicted incidence rate and negatively associated with wealth level for the birth country. Lower country wealth level was also associated with shallower declines in tuberculosis over time. Tuberculosis risks differ by several orders of magnitude within the non-U.S.-born population. A better understanding of these differences will allow more effective targeting of tuberculosis prevention efforts. The methods presented here may also be relevant for understanding tuberculosis trends in other high-income countries.

14.
J Acquir Immune Defic Syndr ; 85(5): 643-650, 2020 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-33177475

RESUMO

BACKGROUND: To assist the Malawi Ministry of Health to evaluate 2 competing strategies for scale-up of isoniazid preventive therapy (IPT) among HIV-positive adults receiving antiretroviral therapy. SETTING: Malawi. METHODS: We used a multidistrict, compartmental model of the Malawi tuberculosis (TB)/HIV epidemic to compare the anticipated health impacts of 6-month versus continuous IPT programs over a 12-year horizon while respecting a US$10.8 million constraint on drug costs in the first 3 years. RESULTS: The 6-month IPT program could be implemented nationwide, whereas the continuous IPT alternative could be introduced in 14 (of the 27) districts. By the end of year 12, the continuous IPT strategy was predicted to avert more TB cases than the 6-month alternative, although not statistically significant (2368 additional cases averted; 95% projection interval [PI], -1459 to 5023). The 6-month strategy required fewer person-years of IPT to avert a case of TB or death than the continuous strategy. For both programs, the mean reductions in TB incidence among people living with HIV by year 12 were expected to be <10%, and the cumulative numbers of IPT-related hepatotoxicity to exceed the number of all-cause deaths averted in the first 3 years. CONCLUSIONS: With the given budgetary constraint, the nationwide implementation of 6-month IPT would be more efficient and yield comparable health benefits than implementing a continuous IPT program in fewer districts. The anticipated health effects associated with both IPT strategies suggested that a combination of different TB intervention strategies would likely be required to yield a greater impact on TB control in settings such as Malawi, where antiretroviral therapycoverage is relatively high.

15.
PLoS Comput Biol ; 16(11): e1008180, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-33137088

RESUMO

Each year in the United States, influenza causes illness in 9.2 to 35.6 million individuals and is responsible for 12,000 to 56,000 deaths. The U.S. Centers for Disease Control and Prevention (CDC) tracks influenza activity through a national surveillance network. These data are only available after a delay of 1 to 2 weeks, and thus influenza epidemiologists and transmission modelers have explored the use of other data sources to produce more timely estimates and predictions of influenza activity. We evaluated whether data collected from a national commercial network of influenza diagnostic machines could produce valid estimates of the current burden and help to predict influenza trends in the United States. Quidel Corporation provided us with de-identified influenza test results transmitted in real-time from a national network of influenza test machines called the Influenza Test System (ITS). We used this ITS dataset to estimate and predict influenza-like illness (ILI) activity in the United States over the 2015-2016 and 2016-2017 influenza seasons. First, we developed linear logistic models on national and regional geographic scales that accurately estimated two CDC influenza metrics: the proportion of influenza test results that are positive and the proportion of physician visits that are ILI-related. We then used our estimated ILI-related proportion of physician visits in transmission models to produce improved predictions of influenza trends in the United States at both the regional and national scale. These findings suggest that ITS can be leveraged to improve "nowcasts" and short-term forecasts of U.S. influenza activity.

16.
BMC Infect Dis ; 20(1): 789, 2020 Oct 23.
Artigo em Inglês | MEDLINE | ID: mdl-33097000

RESUMO

BACKGROUND: People successfully completing treatment for tuberculosis remain at elevated risk for recurrent disease, either from relapse or reinfection. Identifying risk factors for recurrent tuberculosis may help target post-tuberculosis screening and care. METHODS: We enrolled 500 patients with smear-positive pulmonary tuberculosis in South Africa and collected baseline data on demographics, clinical presentation and sputum mycobacterial cultures for 24-loci mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing. We used routinely-collected administrative data to identify recurrent episodes of tuberculosis occurring over a median of six years after successful treatment completion. RESULTS: Of 500 patients initially enrolled, 333 (79%) successfully completed treatment for tuberculosis. During the follow-up period 35 patients with successful treatment (11%) experienced a bacteriologically confirmed tuberculosis recurrence. In our Cox proportional hazards model, a 3+ AFB sputum smear grade was significantly associated with recurrent tuberculosis with a hazard ratio of 3.33 (95% CI 1.44-7.7). The presence of polyclonal M. tuberculosis infection at baseline had a hazard ratio for recurrence of 1.96 (95% CI 0.86-4.48). CONCLUSION: Our results indicate that AFB smear grade is independently associated with tuberculosis recurrence after successful treatment for an initial episode while the association between polyclonal M. tuberculosis infection and increased risk of recurrence appears possible.


Assuntos
Antituberculosos/uso terapêutico , Mycobacterium tuberculosis/genética , Escarro/microbiologia , Tuberculose Pulmonar/tratamento farmacológico , Tuberculose Pulmonar/epidemiologia , Adulto , Feminino , Seguimentos , Genótipo , Humanos , Masculino , Pessoa de Meia-Idade , Repetições Minissatélites/genética , Recidiva , Fatores de Risco , África do Sul/epidemiologia , Resultado do Tratamento , Tuberculose Pulmonar/diagnóstico , Tuberculose Pulmonar/microbiologia , Adulto Jovem
17.
BMC Med ; 18(1): 234, 2020 Sep 02.
Artigo em Inglês | MEDLINE | ID: mdl-32873309

RESUMO

BACKGROUND: Identifying hotspots of tuberculosis transmission can inform spatially targeted active case-finding interventions. While national tuberculosis programs maintain notification registers which represent a potential source of data to investigate transmission patterns, high local tuberculosis incidence may not provide a reliable signal for transmission because the population distribution of covariates affecting susceptibility and disease progression may confound the relationship between tuberculosis incidence and transmission. Child cases of tuberculosis and other endemic infectious disease have been observed to provide a signal of their transmission intensity. We assessed whether local overrepresentation of child cases in tuberculosis notification data corresponds to areas where recent transmission events are concentrated. METHODS: We visualized spatial clustering of children < 5 years old notified to Peru's National Tuberculosis Program from two districts of Lima, Peru, from 2005 to 2007 using a log-Gaussian Cox process to model the intensity of the point-referenced child cases. To identify where clustering of child cases was more extreme than expected by chance alone, we mapped all cases from the notification data onto a grid and used a hierarchical Bayesian spatial model to identify grid cells where the proportion of cases among children < 5 years old is greater than expected. Modeling the proportion of child cases allowed us to use the spatial distribution of adult cases to control for unobserved factors that may explain the spatial variability in the distribution of child cases. We compare where young children are overrepresented in case notification data to areas identified as transmission hotspots using molecular epidemiological methods during a prospective study of tuberculosis transmission conducted from 2009 to 2012 in the same setting. RESULTS: Areas in which childhood tuberculosis cases are overrepresented align with areas of spatial concentration of transmission revealed by molecular epidemiologic methods. CONCLUSIONS: Age-disaggregated notification data can be used to identify hotspots of tuberculosis transmission and suggest local force of infection, providing an easily accessible source of data to target active case-finding intervention.

18.
Artigo em Inglês | MEDLINE | ID: mdl-32925361

RESUMO

BACKGROUND: To assist the Malawi Ministry of Health to evaluate two competing strategies for scale-up of isoniazid preventive therapy (IPT) among HIV-positive adults receiving ART. SETTING: Malawi. METHODS: We used a multi-district, compartmental model of the Malawi TB/HIV epidemic to compare the anticipated health impacts of 6-month versus continuous IPT programs over a 12-year horizon, while respecting a US$10.8 million constraint on drug costs in the first three years. RESULTS: The 6-month IPT program could be implemented nationwide while the continuous IPT alternative could be introduced in 14 (out of 27) districts. By the end of year 12, the continuous IPT strategy was predicted to avert more TB cases than the 6-month alternative, although not statistically significantly (2368 additional cases averted; 95%PI, -1459, 5023). The 6-month strategy required fewer person-years of IPT to avert a case of TB or death than the continuous strategy. For both programs, the mean reductions in TB incidence among PLHIV by year 12 were expected to be <10%, and the cumulative numbers of IPT-related hepatotoxicity to exceed the number of all-cause deaths averted in the first three years. CONCLUSION: With the given budgetary constraint, nationwide implementation of 6-month IPT would be more efficient and yield comparable health benefits than implementing continuous IPT program in fewer districts. The anticipated health effects associated with both IPT strategies suggested a combination of different TB intervention strategies would likely be required to yield greater impact on TB control in settings like Malawi, where ART coverage is relatively high.

19.
Microb Genom ; 6(8)2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32735210

RESUMO

Pathogen genomic data are increasingly used to characterize global and local transmission patterns of important human pathogens and to inform public health interventions. Yet, there is no current consensus on how to measure genomic variation. To test the effect of the variant-identification approach on transmission inferences for Mycobacterium tuberculosis, we conducted an experiment in which five genomic epidemiology groups applied variant-identification pipelines to the same outbreak sequence data. We compared the variants identified by each group in addition to transmission and phylogenetic inferences made with each variant set. To measure the performance of commonly used variant-identification tools, we simulated an outbreak. We compared the performance of three mapping algorithms, five variant callers and two variant filters in recovering true outbreak variants. Finally, we investigated the effect of applying increasingly stringent filters on transmission inferences and phylogenies. We found that variant-calling approaches used by different groups do not recover consistent sets of variants, which can lead to conflicting transmission inferences. Further, performance in recovering true variation varied widely across approaches. While no single variant-identification approach outperforms others in both recovering true genome-wide and outbreak-level variation, variant-identification algorithms calibrated upon real sequence data or that incorporate local reassembly outperform others in recovering true pairwise differences between isolates. The choice of variant filters contributed to extensive differences across pipelines, and applying increasingly stringent filters rapidly eroded the accuracy of transmission inferences and quality of phylogenies reconstructed from outbreak variation. Commonly used approaches to identify M. tuberculosis genomic variation have variable performance, particularly when predicting potential transmission links from pairwise genetic distances. Phylogenetic reconstruction may be improved by less stringent variant filtering. Approaches that improve variant identification in repetitive, hypervariable regions, such as long-read assemblies, may improve transmission inference.

20.
PLoS Comput Biol ; 16(8): e1008106, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32797079

RESUMO

Antibiotic resistance is rising and we urgently need to gain a better quantitative understanding of how antibiotics act, which in turn would also speed up the development of new antibiotics. Here, we describe a computational model (COMBAT-COmputational Model of Bacterial Antibiotic Target-binding) that can quantitatively predict antibiotic dose-response relationships. Our goal is dual: We address a fundamental biological question and investigate how drug-target binding shapes antibiotic action. We also create a tool that can predict antibiotic efficacy a priori. COMBAT requires measurable biochemical parameters of drug-target interaction and can be directly fitted to time-kill curves. As a proof-of-concept, we first investigate the utility of COMBAT with antibiotics belonging to the widely used quinolone class. COMBAT can predict antibiotic efficacy in clinical isolates for quinolones from drug affinity (R2>0.9). To further challenge our approach, we also do the reverse: estimate the magnitude of changes in drug-target binding based on antibiotic dose-response curves. We overexpress target molecules to infer changes in antibiotic-target binding from changes in antimicrobial efficacy of ciprofloxacin with 92-94% accuracy. To test the generality of our approach, we use the beta-lactam ampicillin to predict target molecule occupancy at MIC from antimicrobial action with 90% accuracy. Finally, we apply COMBAT to predict antibiotic concentrations that can select for resistance due to novel resistance mutations. Using ciprofloxacin and ampicillin as well defined test cases, our work demonstrates that drug-target binding is a major predictor of bacterial responses to antibiotics. This is surprising because antibiotic action involves many additional effects downstream of drug-target binding. In addition, COMBAT provides a framework to inform optimal antibiotic dose levels that maximize efficacy and minimize the rise of resistant mutants.


Assuntos
Antibacterianos , Biologia Computacional/métodos , Desenvolvimento de Medicamentos/métodos , Quinolonas , Antibacterianos/química , Antibacterianos/metabolismo , Antibacterianos/farmacologia , Relação Dose-Resposta a Droga , Farmacorresistência Bacteriana/efeitos dos fármacos , Enterobacteriaceae/efeitos dos fármacos , Infecções por Enterobacteriaceae/microbiologia , Humanos , Testes de Sensibilidade Microbiana , Modelos Biológicos , Quinolonas/administração & dosagem , Quinolonas/química , Quinolonas/metabolismo , Quinolonas/farmacologia
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