Incorporating patient reporting patterns to evaluate spatially targeted TB interventions
Copyright © 2020 Elsevier Inc. All rights reserved..
PURPOSE: Tuberculosis (TB) is geographically heterogeneous, and geographic targeting can improve the impact of TB interventions. However, standard TB notification data may not sufficiently capture this heterogeneity. Better understanding of patient reporting patterns (discrepancies between residence and place of presentation) may improve our ability to use notifications to appropriately target interventions.
METHODS: Using demographic data and TB reports from Dhaka North City Corporation and Dhaka South City Corporation, we identified wards of high TB incidence and developed a TB transmission model. We calibrated the model to patient-level data from selected wards under four different reporting pattern assumptions and estimated the relative impact of targeted versus untargeted active case finding.
RESULTS: The impact of geographically targeted interventions varied substantially depending on reporting pattern assumptions. The relative reduction in TB incidence, comparing targeted with untargeted active case finding in Dhaka North City Corporation, was 1.20, assuming weak correlation between reporting and residence, versus 2.45, assuming perfect correlation. Similar patterns were observed in Dhaka South City Corporation (1.03 vs. 2.08).
CONCLUSIONS: Movement of individuals seeking TB diagnoses may substantially affect ward-level TB transmission. Better understanding of patient reporting patterns can improve estimates of the impact of targeted interventions in reducing TB incidence. Incorporating high-quality patient-level data is critical to optimizing TB interventions.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:54 |
|---|---|
| Enthalten in: |
Annals of epidemiology - 54(2021) vom: 01. Feb., Seite 7-10 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Gomes, Isabella [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
Journal Article |
|---|
| Anmerkungen: |
Date Completed 01.03.2021 Date Revised 29.10.2022 published: Print-Electronic Citation Status MEDLINE |
|---|
| doi: |
10.1016/j.annepidem.2020.11.003 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM31734465X |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM31734465X | ||
| 003 | DE-627 | ||
| 005 | 20231225163053.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.1016/j.annepidem.2020.11.003 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1057.xml |
| 035 | |a (DE-627)NLM31734465X | ||
| 035 | |a (NLM)33166716 | ||
| 035 | |a (PII)S1047-2797(20)30410-5 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Gomes, Isabella |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Incorporating patient reporting patterns to evaluate spatially targeted TB interventions |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 01.03.2021 | ||
| 500 | |a Date Revised 29.10.2022 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2020 Elsevier Inc. All rights reserved. | ||
| 520 | |a PURPOSE: Tuberculosis (TB) is geographically heterogeneous, and geographic targeting can improve the impact of TB interventions. However, standard TB notification data may not sufficiently capture this heterogeneity. Better understanding of patient reporting patterns (discrepancies between residence and place of presentation) may improve our ability to use notifications to appropriately target interventions | ||
| 520 | |a METHODS: Using demographic data and TB reports from Dhaka North City Corporation and Dhaka South City Corporation, we identified wards of high TB incidence and developed a TB transmission model. We calibrated the model to patient-level data from selected wards under four different reporting pattern assumptions and estimated the relative impact of targeted versus untargeted active case finding | ||
| 520 | |a RESULTS: The impact of geographically targeted interventions varied substantially depending on reporting pattern assumptions. The relative reduction in TB incidence, comparing targeted with untargeted active case finding in Dhaka North City Corporation, was 1.20, assuming weak correlation between reporting and residence, versus 2.45, assuming perfect correlation. Similar patterns were observed in Dhaka South City Corporation (1.03 vs. 2.08) | ||
| 520 | |a CONCLUSIONS: Movement of individuals seeking TB diagnoses may substantially affect ward-level TB transmission. Better understanding of patient reporting patterns can improve estimates of the impact of targeted interventions in reducing TB incidence. Incorporating high-quality patient-level data is critical to optimizing TB interventions | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, U.S. Gov't, Non-P.H.S. | |
| 650 | 4 | |a Tuberculosis heterogeneity | |
| 650 | 4 | |a Tuberculosis in Dhaka | |
| 650 | 4 | |a Tuberculosis patient-level reporting | |
| 700 | 1 | |a Reja, Mehdi |e verfasserin |4 aut | |
| 700 | 1 | |a Shrestha, Sourya |e verfasserin |4 aut | |
| 700 | 1 | |a Pennington, Jeffrey |e verfasserin |4 aut | |
| 700 | 1 | |a Jo, Youngji |e verfasserin |4 aut | |
| 700 | 1 | |a Baik, Yeonsoo |e verfasserin |4 aut | |
| 700 | 1 | |a Islam, Shamiul |e verfasserin |4 aut | |
| 700 | 1 | |a Khan, Ahmadul Hasan |e verfasserin |4 aut | |
| 700 | 1 | |a Faisel, Abu Jamil |e verfasserin |4 aut | |
| 700 | 1 | |a Cordon, Oscar |e verfasserin |4 aut | |
| 700 | 1 | |a Roy, Tapash |e verfasserin |4 aut | |
| 700 | 1 | |a Suarez, Pedro |e verfasserin |4 aut | |
| 700 | 1 | |a Hussain, Hamidah |e verfasserin |4 aut | |
| 700 | 1 | |a Dowdy, David |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Annals of epidemiology |d 1996 |g 54(2021) vom: 01. Feb., Seite 7-10 |w (DE-627)NLM013235370 |x 1873-2585 |7 nnns |
| 773 | 1 | 8 | |g volume:54 |g year:2021 |g day:01 |g month:02 |g pages:7-10 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.1016/j.annepidem.2020.11.003 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 54 |j 2021 |b 01 |c 02 |h 7-10 | ||