Journal Article > ResearchFull Text
Lancet Child Adolesc Health. 13 March 2023; Online ahead of print; DOI:10.1016/S2352-4642(23)00004-4
Gunasekera KS, Marcy O, Muñoz J, Lopez-Varela E, Sekadde MP, et al.
Lancet Child Adolesc Health. 13 March 2023; Online ahead of print; DOI:10.1016/S2352-4642(23)00004-4
BACKGROUND
Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres.
METHODS
For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings.
FINDINGS
Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms.
INTERPRETATION
We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance.
Many children with pulmonary tuberculosis remain undiagnosed and untreated with related high morbidity and mortality. Recent advances in childhood tuberculosis algorithm development have incorporated prediction modelling, but studies so far have been small and localised, with limited generalisability. We aimed to evaluate the performance of currently used diagnostic algorithms and to use prediction modelling to develop evidence-based algorithms to assist in tuberculosis treatment decision making for children presenting to primary health-care centres.
METHODS
For this meta-analysis, we identified individual participant data from a WHO public call for data on the management of tuberculosis in children and adolescents and referral from childhood tuberculosis experts. We included studies that prospectively recruited consecutive participants younger than 10 years attending health-care centres in countries with a high tuberculosis incidence for clinical evaluation of pulmonary tuberculosis. We collated individual participant data including clinical, bacteriological, and radiological information and a standardised reference classification of pulmonary tuberculosis. Using this dataset, we first retrospectively evaluated the performance of several existing treatment-decision algorithms. We then used the data to develop two multivariable prediction models that included features used in clinical evaluation of pulmonary tuberculosis-one with chest x-ray features and one without-and we investigated each model's generalisability using internal-external cross-validation. The parameter coefficient estimates of the two models were scaled into two scoring systems to classify tuberculosis with a prespecified sensitivity target. The two scoring systems were used to develop two pragmatic, treatment-decision algorithms for use in primary health-care settings.
FINDINGS
Of 4718 children from 13 studies from 12 countries, 1811 (38·4%) were classified as having pulmonary tuberculosis: 541 (29·9%) bacteriologically confirmed and 1270 (70·1%) unconfirmed. Existing treatment-decision algorithms had highly variable diagnostic performance. The scoring system derived from the prediction model that included clinical features and features from chest x-ray had a combined sensitivity of 0·86 [95% CI 0·68-0·94] and specificity of 0·37 [0·15-0·66] against a composite reference standard. The scoring system derived from the model that included only clinical features had a combined sensitivity of 0·84 [95% CI 0·66-0·93] and specificity of 0·30 [0·13-0·56] against a composite reference standard. The scoring system from each model was placed after triage steps, including assessment of illness acuity and risk of poor tuberculosis-related outcomes, to develop treatment-decision algorithms.
INTERPRETATION
We adopted an evidence-based approach to develop pragmatic algorithms to guide tuberculosis treatment decisions in children, irrespective of the resources locally available. This approach will empower health workers in primary health-care settings with high tuberculosis incidence and limited resources to initiate tuberculosis treatment in children to improve access to care and reduce tuberculosis-related mortality. These algorithms have been included in the operational handbook accompanying the latest WHO guidelines on the management of tuberculosis in children and adolescents. Future prospective evaluation of algorithms, including those developed in this work, is necessary to investigate clinical performance.
Journal Article > CommentaryFull Text
Lancet Infect Dis. 1 February 2017 (Issue 2)
Smith JS
Lancet Infect Dis. 1 February 2017 (Issue 2)
Conference Material > Abstract
Truelove SA, Hedge S, Kostandova N, Niehaus L, Rao B, et al.
MSF Scientific Days International 2021: Research. 18 May 2021
INTRODUCTION
Since the emergence of the COVID-19 pandemic, concerns have arisen regarding the potential impact of outbreaks affecting Rohingya refugees living in the Kutupalong-Balukhali refugee camps in Bangladesh. Early modeling work projected substantial outbreaks of SARS-CoV-2 virus were likely within the camps. However only 435 laboratory-confirmed cases and 10 deaths were reported from 14 May 2020 through 19 March 2021. While these official numbers imply spread of SARS-CoV-2 has been controlled, other data are contradictory, highlighting a population unwilling to seek care or be tested. Surveys from slums in India and Bangladesh suggest seroprevalence rates of 45% and 75%. Here we use multiple data sources to evaluate whether SARS-CoV-2 outbreaks may in fact have been larger than previously thought among Rohingya refugees in the Kutupalong-Balukhali camps.
METHODS
We used a mixed-methods approach to analyze SARSCoV-2 transmission in the Kutupalong-Balukhali refugee camps using multiple datasets. We developed a probabilistic inference framework to assess support for three hypotheses of how variability in care seeking and testing might alter the interpretation of official case and testing data. We estimated weekly numbers of infections among the Rohingya refugees using official reported case and testing data, data on acute respiratory infections (ARI) from WHO’s Emergency Warning and Response System, probability of SARS-CoV-2 PCR test among ARI cases at MSF health centres, and data from a serological survey conducted in Dhaka. Separately, we assessed compatibility with suspected COVID-19 among deaths identified through an International Organization for Migration (IOM) mortality survey among the Rohingya during April–July 2020. We compare these deaths to the inference model results to identify consistency between sources and methods.
ETHICS
This study fulfilled the exemption criteria set by the MSF Ethics Review Board (ERB) for a posteriori analyses of routinely collected clinical data and thus did not require MSF ERB review. It was conducted with permission from Dr Kiran Jobanputra, Operational Centre Amsterdam, MSF.
RESULTS
Under our probability framework, each hypothesis suggests a substantial outbreak occurred, though size and timing vary substantially. Under hypotheses accounting for declines in willingness to seek care, the data suggest a large outbreak occurred in spring 2020, with up to 400,000 infections, or 47% of the population, and 390 deaths occurring during April-December 2020. These findings were consistent in both timing and magnitude of the outbreak estimated separately from deaths identified by the IOM survey, including 47 unreported deaths consistent with suspected COVID-19 and up to 370 suspected COVID-19 deaths after adjusting for sampling. These deaths coincided temporally with spikes in reported cases and test-positivity rates during June 2020 and with increased contact during Ramadan.
CONCLUSIONS
Despite the low numbers of reported cases and deaths, we suggest an early large-scale outbreak is consistent with the reported data, with the outbreak remaining unobserved because of reduced care-seeking behavior and low infection severity among this population. Current data do not permit precise estimation of incidence, but results do suggest substantial unrecognized transmission of SARS-CoV-2 within the camps. However, confirmation will await more conclusive evidence from serological testing.
CONFLICTS OF INTEREST
None declared.
Since the emergence of the COVID-19 pandemic, concerns have arisen regarding the potential impact of outbreaks affecting Rohingya refugees living in the Kutupalong-Balukhali refugee camps in Bangladesh. Early modeling work projected substantial outbreaks of SARS-CoV-2 virus were likely within the camps. However only 435 laboratory-confirmed cases and 10 deaths were reported from 14 May 2020 through 19 March 2021. While these official numbers imply spread of SARS-CoV-2 has been controlled, other data are contradictory, highlighting a population unwilling to seek care or be tested. Surveys from slums in India and Bangladesh suggest seroprevalence rates of 45% and 75%. Here we use multiple data sources to evaluate whether SARS-CoV-2 outbreaks may in fact have been larger than previously thought among Rohingya refugees in the Kutupalong-Balukhali camps.
METHODS
We used a mixed-methods approach to analyze SARSCoV-2 transmission in the Kutupalong-Balukhali refugee camps using multiple datasets. We developed a probabilistic inference framework to assess support for three hypotheses of how variability in care seeking and testing might alter the interpretation of official case and testing data. We estimated weekly numbers of infections among the Rohingya refugees using official reported case and testing data, data on acute respiratory infections (ARI) from WHO’s Emergency Warning and Response System, probability of SARS-CoV-2 PCR test among ARI cases at MSF health centres, and data from a serological survey conducted in Dhaka. Separately, we assessed compatibility with suspected COVID-19 among deaths identified through an International Organization for Migration (IOM) mortality survey among the Rohingya during April–July 2020. We compare these deaths to the inference model results to identify consistency between sources and methods.
ETHICS
This study fulfilled the exemption criteria set by the MSF Ethics Review Board (ERB) for a posteriori analyses of routinely collected clinical data and thus did not require MSF ERB review. It was conducted with permission from Dr Kiran Jobanputra, Operational Centre Amsterdam, MSF.
RESULTS
Under our probability framework, each hypothesis suggests a substantial outbreak occurred, though size and timing vary substantially. Under hypotheses accounting for declines in willingness to seek care, the data suggest a large outbreak occurred in spring 2020, with up to 400,000 infections, or 47% of the population, and 390 deaths occurring during April-December 2020. These findings were consistent in both timing and magnitude of the outbreak estimated separately from deaths identified by the IOM survey, including 47 unreported deaths consistent with suspected COVID-19 and up to 370 suspected COVID-19 deaths after adjusting for sampling. These deaths coincided temporally with spikes in reported cases and test-positivity rates during June 2020 and with increased contact during Ramadan.
CONCLUSIONS
Despite the low numbers of reported cases and deaths, we suggest an early large-scale outbreak is consistent with the reported data, with the outbreak remaining unobserved because of reduced care-seeking behavior and low infection severity among this population. Current data do not permit precise estimation of incidence, but results do suggest substantial unrecognized transmission of SARS-CoV-2 within the camps. However, confirmation will await more conclusive evidence from serological testing.
CONFLICTS OF INTEREST
None declared.
Journal Article > ReviewFull Text
J Migr Health. 29 October 2021; Volume 4; 100071.; DOI:10.1016/j.jmh.2021.100071
Cantor D, Swartz J, Roberts B, Abbara A, Ager A, et al.
J Migr Health. 29 October 2021; Volume 4; 100071.; DOI:10.1016/j.jmh.2021.100071
We seek to strengthen understanding of the health needs of internally displaced persons (IDPs) in contexts of conflict or violence. Based upon a scoping review, our paper identified limited evidence on IDP health, but nevertheless indicates that IDPs tend to experience worse health outcomes than other conflict-affected populations across a range of health issues; and this is due to the particularly vulnerable situation of IDPs relative to these other populations, including reduced access to health services. Further research is required to better understand these needs and the interventions that can most effectively address these needs.
Journal Article > CommentaryFull Text
Lancet Global Health. 1 April 2020; Volume 8 (Issue 4); DOI:10.1016/S2214-109X(20)30030-9
Smith JS, Whitehouse K, Blanchet K
Lancet Global Health. 1 April 2020; Volume 8 (Issue 4); DOI:10.1016/S2214-109X(20)30030-9
Journal Article > LetterFull Text
Lancet. 11 March 2017; Volume 389 (Issue 10073); 1007-1008.; DOI:10.1016/S0140-6736(17)30660-8
Smith JS, Aloudat T
Lancet. 11 March 2017; Volume 389 (Issue 10073); 1007-1008.; DOI:10.1016/S0140-6736(17)30660-8
Journal Article > ResearchAbstract Only
Eur Respir J. 17 June 2021; Volume 59 (Issue 1); 2101116.; DOI:10.1183/13993003.01116-2021
Orikiriza P, Smith JS, Ssekyanzi B, Nyehangane D, Mugisha IT, et al.
Eur Respir J. 17 June 2021; Volume 59 (Issue 1); 2101116.; DOI:10.1183/13993003.01116-2021
BACKGROUND
Non-sputum-based diagnostic approaches are crucial in children at high risk of disseminated tuberculosis (TB) who cannot expectorate sputum. We evaluated the diagnostic accuracy of stool Xpert MTB/RIF and urine AlereLAM tests in this group of children.
METHODS
Hospitalised children with presumptive TB and either age <2 years, HIV-positive or with severe malnutrition were enrolled in a diagnostic cohort. At enrolment, we attempted to collect two urine, two stool and two respiratory samples. Urine and stool were tested with AlereLAM and Xpert MTB/RIF, respectively. Respiratory samples were tested with Xpert MTB/RIF and mycobacterial culture. Both a microbiological and a composite clinical reference standard were used.
RESULTS
The study analysed 219 children; median age 16.4 months, 72 (32.9%) HIV-positive and 184 (84.4%) severely malnourished. 12 (5.5%) and 58 (28.5%) children had confirmed and unconfirmed TB, respectively. Stool and urine were collected in 219 (100%) and 216 (98.6%) children, respectively. Against the microbiological reference standard, the sensitivity and specificity of stool Xpert MTB/RIF was 50.0% (6/12, 95% CI 21.1–78.9%) and 99.1% (198/200, 95% 96.4–99.9%), while that of urine AlereLAM was 50.0% (6/12, 95% 21.1–78.9%) and 74.6% (147/197, 95% 67.9–80.5%), respectively. Against the composite reference standard, sensitivity was reduced to 11.4% (8/70) for stool and 26.2% (17/68) for urine, with no major difference by age group (<2 and ≥2 years) or HIV status.
CONCLUSIONS
The Xpert MTB/RIF assay has excellent specificity on stool, but sensitivity is suboptimal. Urine AlereLAM is compromised by poor sensitivity and specificity in children.
Non-sputum-based diagnostic approaches are crucial in children at high risk of disseminated tuberculosis (TB) who cannot expectorate sputum. We evaluated the diagnostic accuracy of stool Xpert MTB/RIF and urine AlereLAM tests in this group of children.
METHODS
Hospitalised children with presumptive TB and either age <2 years, HIV-positive or with severe malnutrition were enrolled in a diagnostic cohort. At enrolment, we attempted to collect two urine, two stool and two respiratory samples. Urine and stool were tested with AlereLAM and Xpert MTB/RIF, respectively. Respiratory samples were tested with Xpert MTB/RIF and mycobacterial culture. Both a microbiological and a composite clinical reference standard were used.
RESULTS
The study analysed 219 children; median age 16.4 months, 72 (32.9%) HIV-positive and 184 (84.4%) severely malnourished. 12 (5.5%) and 58 (28.5%) children had confirmed and unconfirmed TB, respectively. Stool and urine were collected in 219 (100%) and 216 (98.6%) children, respectively. Against the microbiological reference standard, the sensitivity and specificity of stool Xpert MTB/RIF was 50.0% (6/12, 95% CI 21.1–78.9%) and 99.1% (198/200, 95% 96.4–99.9%), while that of urine AlereLAM was 50.0% (6/12, 95% 21.1–78.9%) and 74.6% (147/197, 95% 67.9–80.5%), respectively. Against the composite reference standard, sensitivity was reduced to 11.4% (8/70) for stool and 26.2% (17/68) for urine, with no major difference by age group (<2 and ≥2 years) or HIV status.
CONCLUSIONS
The Xpert MTB/RIF assay has excellent specificity on stool, but sensitivity is suboptimal. Urine AlereLAM is compromised by poor sensitivity and specificity in children.
Journal Article > ResearchFull Text
J Migr Health. 31 December 2021; Volume 5 (Issue 5); 100090.; DOI:10.1016/j.jmh.2022.100090
Roberts B, Ekezie W, Jobanputra K, Smith JS, Ellithy S, et al.
J Migr Health. 31 December 2021; Volume 5 (Issue 5); 100090.; DOI:10.1016/j.jmh.2022.100090
BACKGROUND
There are an estimated 55 million internally displaced persons (IDPs) globally. IDPs commonly have worse health outcomes than host populations and other forcibly displaced populations such as refugees. Official development assistance (ODA) is a major source of the global financial response for health in low- and middle-income countries (LMICs), including for populations affected by armed conflict and forced displacement. Analysis of ODA supports efforts to improve donor accountability, transparency and the equitable use of ODA. The aim of this study is to examine international donor support and responsiveness to IDP health needs through analysis of ODA disbursements to LMICs between 2010 and 2019.
METHODS
ODA disbursement data to LMICs from 2010 to 2019 were extracted from the Creditor Reporting System (CRS) database and analysed with Stata software using a combination of: (i) text searching for IDP and refugee related terms; and (ii) relevant health and humanitarian CRS purpose codes. Descriptive analysis was used to examine patterns of ODA disbursement, and nonlinear least squared regression analysis was used to examine responsiveness of ODA disbursement to recipient country IDP population size and health system capacity and health characteristics.
FINDINGS
The study highlighted declining per IDP capita health ODA from USD 5.34 in 2010 to USD 3.72 in 2019 (with annual average decline of -38% from the 2010 baseline). In contrast, health ODA for refugees in LMICs increased from USD 18.55 in 2010 to USD 23.31 in 2019 (with an annual average increase of +14%). Certain health topics for IDPs received very low ODA, with only 0.44% of IDP health ODA disbursed for non-communicable diseases (including mental health). There was also weak evidence of IDP health ODA being related to recipient country IDP population size, and health system capacity and health characteristics. The paper highlights the need for increased investment by donors in IDP health ODA and to ensure that it is responsive to their health needs.
There are an estimated 55 million internally displaced persons (IDPs) globally. IDPs commonly have worse health outcomes than host populations and other forcibly displaced populations such as refugees. Official development assistance (ODA) is a major source of the global financial response for health in low- and middle-income countries (LMICs), including for populations affected by armed conflict and forced displacement. Analysis of ODA supports efforts to improve donor accountability, transparency and the equitable use of ODA. The aim of this study is to examine international donor support and responsiveness to IDP health needs through analysis of ODA disbursements to LMICs between 2010 and 2019.
METHODS
ODA disbursement data to LMICs from 2010 to 2019 were extracted from the Creditor Reporting System (CRS) database and analysed with Stata software using a combination of: (i) text searching for IDP and refugee related terms; and (ii) relevant health and humanitarian CRS purpose codes. Descriptive analysis was used to examine patterns of ODA disbursement, and nonlinear least squared regression analysis was used to examine responsiveness of ODA disbursement to recipient country IDP population size and health system capacity and health characteristics.
FINDINGS
The study highlighted declining per IDP capita health ODA from USD 5.34 in 2010 to USD 3.72 in 2019 (with annual average decline of -38% from the 2010 baseline). In contrast, health ODA for refugees in LMICs increased from USD 18.55 in 2010 to USD 23.31 in 2019 (with an annual average increase of +14%). Certain health topics for IDPs received very low ODA, with only 0.44% of IDP health ODA disbursed for non-communicable diseases (including mental health). There was also weak evidence of IDP health ODA being related to recipient country IDP population size, and health system capacity and health characteristics. The paper highlights the need for increased investment by donors in IDP health ODA and to ensure that it is responsive to their health needs.
Journal Article > EditorialFull Text
Palliat Med. 1 February 2017; Volume 31 (Issue 2); 99-101.; DOI:10.1177/0269216316686258
Smith JS, Aloudat T
Palliat Med. 1 February 2017; Volume 31 (Issue 2); 99-101.; DOI:10.1177/0269216316686258
Journal Article > ResearchFull Text
Public Health Action. 25 April 2018; Volume 8 (Issue Suppl 1); S44-S49.; DOI:10.5588/pha.17.0077
Mumbengegwi DR, Sturrock H, Hsiang M, Roberts K, Kleinschmidt I, et al.
Public Health Action. 25 April 2018; Volume 8 (Issue Suppl 1); S44-S49.; DOI:10.5588/pha.17.0077
SETTING
A comparison of routine Namibia National Malaria Programme data (reported) vs. household survey data (administrative) on indoor residual spraying (IRS) in western Zambezi region, Namibia, for the 2014-2015 malaria season.
OBJECTIVES
To determine 1) IRS coverage (administrative and reported), 2) its effect on malaria incidence, and 3) reasons for non-uptake of IRS in western Zambezi region, Namibia, for the 2014-2015 malaria season. Design: This was a descriptive study.
RESULTS
IRS coverage in western Zambezi region was low, ranging from 42.3% to 52.2% for administrative coverage vs. 45.9-66.7% for reported coverage. There was no significant correlation between IRS coverage and malaria incidence for this region (r = -0.45, P = 0.22). The main reasons for households not being sprayed were that residents were not at home during spraying times or that spray operators did not visit the households.
CONCLUSIONS
IRS coverage in western Zambezi region, Namibia, was low during the 2014-2015 malaria season because of poor community engagement and awareness of times for spray operations within communities. Higher IRS coverage could be achieved through improved community engagement. Better targeting of the highest risk areas by the use of malaria surveillance will be required to mitigate malaria transmission.
A comparison of routine Namibia National Malaria Programme data (reported) vs. household survey data (administrative) on indoor residual spraying (IRS) in western Zambezi region, Namibia, for the 2014-2015 malaria season.
OBJECTIVES
To determine 1) IRS coverage (administrative and reported), 2) its effect on malaria incidence, and 3) reasons for non-uptake of IRS in western Zambezi region, Namibia, for the 2014-2015 malaria season. Design: This was a descriptive study.
RESULTS
IRS coverage in western Zambezi region was low, ranging from 42.3% to 52.2% for administrative coverage vs. 45.9-66.7% for reported coverage. There was no significant correlation between IRS coverage and malaria incidence for this region (r = -0.45, P = 0.22). The main reasons for households not being sprayed were that residents were not at home during spraying times or that spray operators did not visit the households.
CONCLUSIONS
IRS coverage in western Zambezi region, Namibia, was low during the 2014-2015 malaria season because of poor community engagement and awareness of times for spray operations within communities. Higher IRS coverage could be achieved through improved community engagement. Better targeting of the highest risk areas by the use of malaria surveillance will be required to mitigate malaria transmission.