Dataset Information

Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa.

ABSTRACT: Patterns of transmission of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases worldwide in 2017. Modeling TB transmission networks can provide insight into drivers of transmission, but incomplete sampling of TB cases can pose challenges for inference from individual epidemiologic and molecular data. We assessed the effect of missing cases on a transmission network inferred from Mycobacterium tuberculosis sequencing data on extensively drug-resistant TB cases in KwaZulu-Natal, South Africa, diagnosed in 2011-2014. We tested scenarios in which cases were missing at random, missing differentially by clinical characteristics, or missing differentially by transmission (i.e., cases with many links were under- or oversampled). Under the assumption that cases were missing randomly, the mean number of transmissions per case in the complete network needed to be larger than 20, far higher than expected, to reproduce the observed network. Instead, the most likely scenario involved undersampling of high-transmitting cases, and models provided evidence for super-spreading. To our knowledge, this is the first analysis to have assessed support for different mechanisms of missingness in a TB transmission study, but our results are subject to the distributional assumptions of the network models we used. Transmission studies should consider the potential biases introduced by incomplete sampling and identify host, pathogen, or environmental factors driving super-spreading.

SUBMITTER: Nelson KN

PROVIDER: S-EPMC7443195 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa.

Nelson Kristin N KN Gandhi Neel R NR Mathema Barun B Lopman Benjamin A BA Brust James C M JCM Auld Sara C SC Ismail Nazir N Omar Shaheed Vally SV Brown Tyler S TS Allana Salim S Campbell Angie A Moodley Pravi P Mlisana Koleka K Shah N Sarita NS Jenness Samuel M SM

American journal of epidemiology 20200701 7

Patterns of transmission of drug-resistant tuberculosis (TB) remain poorly understood, despite over half a million incident cases worldwide in 2017. Modeling TB transmission networks can provide insight into drivers of transmission, but incomplete sampling of TB cases can pose challenges for inference from individual epidemiologic and molecular data. We assessed the effect of missing cases on a transmission network inferred from Mycobacterium tuberculosis sequencing data on extensively drug-resi ...[more]

PMID: 32242216

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Project description:BackgroundDrug-resistant tuberculosis threatens recent gains in the treatment of tuberculosis and human immunodeficiency virus (HIV) infection worldwide. A widespread epidemic of extensively drug-resistant (XDR) tuberculosis is occurring in South Africa, where cases have increased substantially since 2002. The factors driving this rapid increase have not been fully elucidated, but such knowledge is needed to guide public health interventions.MethodsWe conducted a prospective study involving 404 participants in KwaZulu-Natal Province, South Africa, with a diagnosis of XDR tuberculosis between 2011 and 2014. Interviews and medical-record reviews were used to elicit information on the participants' history of tuberculosis and HIV infection, hospitalizations, and social networks. Mycobacterium tuberculosis isolates underwent insertion sequence (IS)6110 restriction-fragment-length polymorphism analysis, targeted gene sequencing, and whole-genome sequencing. We used clinical and genotypic case definitions to calculate the proportion of cases of XDR tuberculosis that were due to inadequate treatment of multidrug-resistant (MDR) tuberculosis (i.e., acquired resistance) versus those that were due to transmission (i.e., transmitted resistance). We used social-network analysis to identify community and hospital locations of transmission.ResultsOf the 404 participants, 311 (77%) had HIV infection; the median CD4+ count was 340 cells per cubic millimeter (interquartile range, 117 to 431). A total of 280 participants (69%) had never received treatment for MDR tuberculosis. Genotypic analysis in 386 participants revealed that 323 (84%) belonged to 1 of 31 clusters. Clusters ranged from 2 to 14 participants, except for 1 large cluster of 212 participants (55%) with a LAM4/KZN strain. Person-to-person or hospital-based epidemiologic links were identified in 123 of 404 participants (30%).ConclusionsThe majority of cases of XDR tuberculosis in KwaZulu-Natal, South Africa, an area with a high tuberculosis burden, were probably due to transmission rather than to inadequate treatment of MDR tuberculosis. These data suggest that control of the epidemic of drug-resistant tuberculosis requires an increased focus on interrupting transmission. (Funded by the National Institute of Allergy and Infectious Diseases and others.).

Project description:BackgroundIn South Africa malaria is endemic in Mpumalanga, Limpopo and the north-eastern areas of KwaZulu-Natal provinces. South Africa has set targets to eliminate malaria by 2018 and research into complementary vector control tools such as the Sterile Insect Technique (SIT) is ongoing. It is important to understand community perceptions regarding malaria transmission and control interventions to enable development of community awareness campaign messages appropriate to the needs of the community. We aimed to assess knowledge, attitudes, and practices regarding malaria transmission to inform a public awareness campaign for SIT in Jozini Local Municipality, Mamfene in KwaZulu-Natal province.MethodsWe conducted a cross-sectional survey in three communities in Mamfene, KwaZulu-Natal during 2015. A structured field piloted questionnaire was administered to 400 randomly selected heads of households. Descriptive statistics were used to summarize data.ResultsOf the 400 participants interviewed, 99% had heard about malaria and correctly associated it with mosquito bites. The sources of malaria information were the local health facility (53%), radio (16%) and community meetings (7%). Approximately 63% of the participants were able to identify three or four symptoms of malaria. The majority (76%) were confident that indoor residual spraying (IRS) kills mosquitoes and prevents infection. Bed nets were used by 2% of the participants. SIT knowledge was poor (9%), however 63% of the participants were supportive of mosquito releases for research purposes. The remaining 37% raised concerns and fears, including fear of the unknown and lack of information on the SIT.ConclusionAppropriate knowledge, positive attitude and acceptable treatment-seeking behaviour for malaria were demonstrated by members of the community. Community involvement will be crucial in achieving success of the SIT and future studies should further investigate concerns raised by the community. The existing communication channels used by the malaria control program can be used; however additional channels should be investigated.

Project description:ObjectivesResearch on migration and HIV has largely focused on male migration, often failing to measure HIV risks associated with migration for women. We aimed to establish whether associations between migration and HIV infection differ for women and men, and identify possible mechanisms by which women's migration contributes to their high infection risk.DesignData on socio-demographic characteristics, patterns of migration, sexual behavior and HIV infection status were obtained for a population of 11,677 women aged 15-49 and men aged 15-54, resident members of households within a demographic surveillance area participating in HIV surveillance in 2003-04.MethodsLogistic regression was conducted to examine whether sex and migration were independently associated with HIV infection in three additive effects models, using measures of recent migration, household presence and migration frequency. Multiplicative effects models were fitted to explore whether the risk of HIV associated with migration differed for males and females. Further modeling and simulations explored whether composition or behavioral differences accounted for observed associations.ResultsRelative to non-migrant males, non-migrant females had higher odds of being HIV-positive (adjusted odds ratio [aOR] = 1.72; 95% confidence interval [1.49-1.99]), but odds were higher for female migrants (aOR = 2.55 [2.07-3.13]). Female migrants also had higher odds of infection relative to female non-migrants (aOR = 1.48 [1.23-1.77]). The association between number of sexual partners over the lifetime and HIV infection was modified by both sex and migrant status: For male non-migrants, each additional partner was associated with 3% higher odds of HIV infection (aOR = 1.03 [1.02-1.05]); for male migrants the association between number of partners and HIV infection was non-significant. Each additional partner increased odds of HIV infection by 22% for female non-migrants (aOR = 1.22 [1.12-1.32]) and 46% for female migrants (aOR = 1.46 [1.25-1.69]).ConclusionsHigher risk sexual behavior in the context of migration increased women's likelihood of HIV infection.

Project description:The incidence of HIV infection in young women in Africa is very high. We did a large-scale community-wide phylogenetic study to examine the underlying HIV transmission dynamics and the source and consequences of high rates of HIV infection in young women in South Africa.We did a cross-sectional household survey of randomly selected individuals aged 15-49 years in two neighbouring subdistricts (one urban and one rural) with a high burden of HIV infection in KwaZulu-Natal, South Africa. Participants completed structured questionnaires that captured general demographic, socioeconomic, psychosocial, and behavioural data. Peripheral blood samples were obtained for HIV antibody testing. Samples with HIV RNA viral load greater than 1000 copies per mL were selected for genotyping. We constructed a phylogenetic tree to identify clusters of linked infections (defined as two or more sequences with bootstrap or posterior support ?90% and genetic distance ?4·5%).From June 11, 2014, to June 22, 2015, we enrolled 9812 participants, 3969 of whom tested HIV positive. HIV prevalence (weighted) was 59·8% in 2835 women aged 25-40 years, 40·3% in 1548 men aged 25-40 years, 22·3% in 2224 women younger than 25 years, and 7·6% in 1472 men younger than 25 years. HIV genotyping was done in 1589 individuals with a viral load of more than 1000 copies per mL. In 90 transmission clusters, 123 women were linked to 103 men. Of 60 possible phylogenetically linked pairings with the 43 women younger than 25 years, 18 (30·0%) probable male partners were younger than 25 years, 37 (61·7%) were aged 25-40 years, and five (8·3%) were aged 41-49 years: mean age difference 8·7 years (95% CI 6·8-10·6; p<0·0001). For the 92 possible phylogenetically linked pairings with the 56 women aged 25-40 years, the age difference dropped to 1·1 years (95% CI -0·6 to 2·8; p=0·111). 16 (39·0%) of 41 probable male partners linked to women younger than 25 years were also linked to women aged 25-40 years. Of 79 men (mean age 31·5 years) linked to women younger than 40 years, 62 (78·5%) were unaware of their HIV-positive status, 76 (96·2%) were not on antiretroviral therapy, and 29 (36·7%) had viral loads of more than 50?000 copies per mL.Sexual partnering between young women and older men, who might have acquired HIV from women of similar age, is a key feature of the sexual networks driving transmission. Expansion of treatment and combination prevention strategies that include interventions to address age-disparate sexual partnering is crucial to reducing HIV incidence and enabling Africa to reach the goal of ending AIDS as a public health threat.President's Emergency Program for AIDS Relief, US Centers for Disease Control and Prevention, South African Medical Research Council, and MAC AIDS Fund.

Dataset Information

Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa.

Publications

Modeling Missing Cases and Transmission Links in Networks of Extensively Drug-Resistant Tuberculosis in KwaZulu-Natal, South Africa.

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