Spatial overlap links seemingly unconnected genotype-matched TB cases in rural Uganda

<div><p>Introduction</p><p>Incomplete understanding of TB transmission dynamics in high HIV prevalence settings remains an obstacle for prevention. Understanding where transmission occurs could provide a platform for case finding and interrupting transmission.</p><p>Methods</p><p>From 2012–2015, we sought to recruit all adults starting TB treatment in a Ugandan community. Participants underwent household (HH) contact investigation, and provided names of social contacts, sites of work, healthcare and socializing, and two sputum samples. <i>Mycobacterium tuberculosis</i> culture-positive specimens underwent 24-loci MIRU-VNTR and spoligotyping. We sought to identify epidemiologic links between genotype-matched cases by analyzing social networks and mapping locations where cases reported spending ≥12 hours over the one-month pre-treatment. Sites of spatial overlap (≤100m) between genotype-matched cases were considered potential transmission sites. We analyzed social networks stratified by genotype clustering status, with cases linked by shared locations, and compared network density by location type between clustered vs. non-clustered cases.</p><p>Results</p><p>Of 173 adults with TB, 131 (76%) were enrolled, 108 provided sputum, and 84/131 (78%) were MTB culture-positive: 52% (66/131) tested HIV-positive. Of 118 adult HH contacts, 105 (89%) were screened and 3 (2.5%) diagnosed with active TB. Overall, 33 TB cases (39%) belonged to 15 distinct MTB genotype-matched clusters. Within each cluster, no cases shared a HH or reported shared non-HH contacts. In 6/15 (40%) clusters, potential epidemiologic links were identified by spatial overlap at specific locations: 5/6 involved health care settings. Genotype-clustered TB social networks had significantly greater network density based on shared clinics (p<0.001) and decreased density based on shared marketplaces (p<0.001), compared to non-clustered networks.</p><p>Conclusions</p><p>In this molecular epidemiologic study, links between MTB genotype-matched cases were only identifiable via shared locations, healthcare locations in particular, rather than named contacts. This suggests most transmission is occurring between casual contacts, and emphasizes the need for improved infection control in healthcare settings in rural Africa.</p></div

Demographic and clinical characteristics of MTB genotype non-clustered vs. clustered TB cases.

<p>Demographic and clinical characteristics of MTB genotype non-clustered vs. clustered TB cases.</p

Maps of potential sites of TB transmission within MTB Genotype Clusters 1 and 14, based on geographically adjacent locations of work, healthcare, household or social locations–with each location point color corresponding to a TB patient.

<p>Yellow, green and blue circles show buffer zones of 25 meters (m), 50m and 100m respectively, around each mapped location. The arrows in Panel A show that within MTB Genotype Cluster 1, one work location named by a TB patient (red circle) was <100m from two social venues (black triangles) named by another patient. Panel B shows that within Genotype Cluster 14, one TB patient’s clinical location was adjacent (<50m) to a social location visited by another TB patient.</p

Potential epidemiologic links among patients in six of 15 MTB genotype clusters based on either co-location at a shared site or time spent at geographically adjacent locations (within 100 meters of one another) in the time leading up to TB diagnosis, using GPS coordinates of sites of work, clinic, socializing, and household.

<p>Patients in the remaining nine of 15 MTB genotype clusters had no shared or neighboring locations identified.</p

MapGIS支持下1∶5万地质图建库的关键技术[J]

针对1∶5万地质图建库中的关键问题,结合实践经验,详细阐述了在MapGIS环境下地质图建库的方法、流程和关键技术;系统总结了建库中的常见问题及其处理方法;并通过西峡、淅川等地的1∶5万地质图建库工程,检验了该方法的合理性和可靠性,为同类项目提供了良好的示范作用

Time spent per location type of non-clustered vs. clustered TB cases.

<p>Time spent per location type of non-clustered vs. clustered TB cases.</p

Comparative network density of MTB genotype-clustered and non-clustered TB cases, within social-location networks (i.e. networks included named locations as nodes).

<p>Network density here defined as the proportion of potential connections in a network that are actual connections (i.e. higher density represents a higher connectedness among nodes in a network).</p

Social-location networks of genotype-clustered vs. non-clustered TB cases in Tororo, Uganda.

<p>Each network node represents a participant with culture-positive TB, with node size proportional to node degree. Each network edge represents a specific shared location, with edge colors indicating the location type, as indicated in the legend.</p

Characteristics of study participants stratified by number of SP doses reported taken.

a<p>Reported 0 (n = 32) or 1 (n = 202) doses of SP taken during pregnancy.</p>b<p>Reported 2 (n = 320) or 3 (n = 11) doses of SP taken during pregnancy.</p>c<p>High transmission season May–June 2011.</p

Associations between use of IPTp-SP and outcomes at delivery.

a<p>Adjusted for maternal age, gravidity, bednet use, level of education, wealth index, and transmission season.</p>b<p>Any of the following: placental malaria by any detection method, low birth weight, maternal peripheral parasitemia, or maternal anemia.</p