Prevalence of Tuberculosis in Children After Natural Disasters, Bohol, Philippines

Impact of Earthquakes on Lung Health

Earthquakes are catastrophic natural disasters that cause extensive damage to infrastructure and disrupt the lives of millions worldwide. Beyond the immediate physical and psychological damage caused by earthquakes, these events can significantly impact respiratory health. The inhalation of dust, smoke, particulates, toxic gases, and asbestos exposure can lead to various respiratory health pathologies. These include respiratory infections, exacerbations of pre-existing respiratory diseases, chest traumas, and pulmonary and venous thromboembolism. Longitudinal studies are necessary to assess the long-term respiratory health effects in affected populations. By addressing these knowledge gaps, future mitigation strategies and preparedness measures can be developed to minimize the respiratory health impacts of earthquakes and improve the well-being of affected communities. Robust building infrastructure and comprehensive earthquake preparedness are emerging as the most important determinants for not only mitigating building collapse but also significantly reducing the potential health impacts that follow. This comprehensive review aims to provide a systematic overview of the lung health impacts of earthquakes. It highlights the need for further research to identify specific pollutants, air contaminants, and environmental factors contributing to respiratory health issues following earthquakes.

The Impact of Earthquakes on Public Health: A Narrative Review of Infectious Diseases in the Post-Disaster Period Aiming to Disaster Risk Reduction

Earthquakes are among the most impressive natural phenomena with very high potential to set off a chain of effects that significantly affects public health through casualties and injuries. Related disasters are attributed not only to the strong ground motion and coseismic phenomena but also to secondary effects, comprising mainly landslides and tsunamis, among others. All these can create harsh conditions favorable for the emergence of infectious diseases that are capable of causing additional human and economic losses and disruption of the emergency and recovery process. The present study comprises an extensive narrative review of the existing literature on the earthquake-triggered infectious diseases recorded worldwide, along with their symptoms, causative pathogens, associated risk factors, most vulnerable population groups, and prevention strategies. Respiratory, gastrointestinal, and vector-borne diseases, as well as wound and skin infections, are mainly recorded among the earthquake-affected population. Measures for effectively preventing earthquake-triggered infectious diseases are also proposed. One of the widely proposed measures is the establishment of a proper disease surveillance system in order to immediately and effectively identify the pre- and post-disaster occurrence of infectious diseases. This approach significantly contributes to disease trends monitoring, validation of early warning, and support of the emergency response and recovery actions.

The impact of climate change on the risk factors for tuberculosis: A systematic review

BACKGROUND

Tuberculosis (TB) continues to pose a major public health risk in many countries. The current incidence of disease exceeds guidelines proposed by the World Health Organisation and United Nations. Whilst the relationship between climate change and TB has surfaced in recent literature, it remains neglected in global agendas. There is a need to acknowledge TB as a climate-sensitive disease to facilitate its eradication.

OBJECTIVE

To review epidemiological and prediction model studies that explore how climate change may affect the risk factors for TB, as outlined in the Global Tuberculosis Report 2021: HIV infection, diabetes mellitus, undernutrition, overcrowding, poverty, and indoor air pollution.

METHODS

We conducted a systematic literature search of PubMed, Embase, and Scopus databases to identify studies examining the association between climate variables and the risk factors for TB. Each study that satisfied the inclusion criteria was assessed for quality and ethics. Studies then underwent vote-counting and were categorised based on whether an association was found.

RESULTS

53 studies met inclusion criteria and were included in our review. Vote-counting revealed that two out of two studies found a positive association between the examined climate change proxy and HIV, nine out of twelve studies for diabetes, eight out of seventeen studies for undernutrition, four out of five studies for overcrowding, twelve out of fifteen studies for poverty and one out of three studies for indoor air pollution.

DISCUSSION

We found evidence supporting a positive association between climate change and each of the discussed risk factors for TB, excluding indoor air pollution. Our findings suggest that climate change is likely to affect the susceptibility of individuals to TB by increasing the prevalence of its underlying risk factors, particularly in developing countries. This is an evolving field of research that requires further attention in the scientific community.

Screening tests for active pulmonary tuberculosis in children

BACKGROUND

Globally, children under 15 years represent approximately 12% of new tuberculosis cases, but 16% of the estimated 1.4 million deaths. This higher share of mortality highlights the urgent need to develop strategies to improve case detection in this age group and identify children without tuberculosis disease who should be considered for tuberculosis preventive treatment. One such strategy is systematic screening for tuberculosis in high-risk groups.

OBJECTIVES

To estimate the sensitivity and specificity of the presence of one or more tuberculosis symptoms, or symptom combinations; chest radiography (CXR); Xpert MTB/RIF; Xpert Ultra; and combinations of these as screening tests for detecting active pulmonary childhood tuberculosis in the following groups. - Tuberculosis contacts, including household contacts, school contacts, and other close contacts of a person with infectious tuberculosis. - Children living with HIV. - Children with pneumonia. - Other risk groups (e.g. children with a history of previous tuberculosis, malnourished children). - Children in the general population in high tuberculosis burden settings.

SEARCH METHODS

We searched six databases, including the Cochrane Central Register of Controlled Trials, MEDLINE, and Embase, on 14 February 2020 without language restrictions and contacted researchers in the field.

SELECTION CRITERIA

Cross-sectional and cohort studies where at least 75% of children were aged under 15 years. Studies were eligible if conducted for screening rather than diagnosing tuberculosis. Reference standards were microbiological (MRS) and composite reference standard (CRS), which may incorporate symptoms and CXR.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data and assessed study quality using QUADAS-2. We consolidated symptom screens across included studies into groups that used similar combinations of symptoms as follows: one or more of cough, fever, or poor weight gain and one or more of cough, fever, or decreased playfulness. For combination of symptoms, a positive screen was the presence of one or more than one symptom. We used a bivariate model to estimate pooled sensitivity and specificity with 95% confidence intervals (CIs) and performed analyses separately by reference standard. We assessed certainty of evidence using GRADE.

MAIN RESULTS

Nineteen studies assessed the following screens: one symptom (15 studies, 10,097 participants); combinations of symptoms (12 studies, 29,889 participants); CXR (10 studies, 7146 participants); and Xpert MTB/RIF (2 studies, 787 participants). Several studies assessed more than one screening test. No studies assessed Xpert Ultra. For 16 studies (84%), risk of bias for the reference standard domain was unclear owing to concern about incorporation bias. Across other quality domains, risk of bias was generally low. Symptom screen (verified by CRS) One or more of cough, fever, or poor weight gain in tuberculosis contacts (4 studies, tuberculosis prevalence 2% to 13%): pooled sensitivity was 89% (95% CI 52% to 98%; 113 participants; low-certainty evidence) and pooled specificity was 69% (95% CI 51% to 83%; 2582 participants; low-certainty evidence). Of 1000 children where 50 have pulmonary tuberculosis, 339 would be screen-positive, of whom 294 (87%) would not have pulmonary tuberculosis (false positives); 661 would be screen-negative, of whom five (1%) would have pulmonary tuberculosis (false negatives). One or more of cough, fever, or decreased playfulness in children aged under five years, inpatient or outpatient (3 studies, tuberculosis prevalence 3% to 13%): sensitivity ranged from 64% to 76% (106 participants; moderate-certainty evidence) and specificity from 37% to 77% (2339 participants; low-certainty evidence). Of 1000 children where 50 have pulmonary tuberculosis, 251 to 636 would be screen-positive, of whom 219 to 598 (87% to 94%) would not have pulmonary tuberculosis; 364 to 749 would be screen-negative, of whom 12 to 18 (2% to 3%) would have pulmonary tuberculosis. One or more of cough, fever, poor weight gain, or tuberculosis close contact (World Health Organization four-symptom screen) in children living with HIV, outpatient (2 studies, tuberculosis prevalence 3% and 8%): pooled sensitivity was 61% (95% CI 58% to 64%; 1219 screens; moderate-certainty evidence) and pooled specificity was 94% (95% CI 86% to 98%; 201,916 screens; low-certainty evidence). Of 1000 symptom screens where 50 of the screens are on children with pulmonary tuberculosis, 88 would be screen-positive, of which 57 (65%) would be on children who do not have pulmonary tuberculosis; 912 would be screen-negative, of which 19 (2%) would be on children who have pulmonary tuberculosis. CXR (verified by CRS) CXR with any abnormality in tuberculosis contacts (8 studies, tuberculosis prevalence 2% to 25%): pooled sensitivity was 87% (95% CI 75% to 93%; 232 participants; low-certainty evidence) and pooled specificity was 99% (95% CI 68% to 100%; 3281 participants; low-certainty evidence). Of 1000 children, where 50 have pulmonary tuberculosis, 63 would be screen-positive, of whom 19 (30%) would not have pulmonary tuberculosis; 937 would be screen-negative, of whom 6 (1%) would have pulmonary tuberculosis. Xpert MTB/RIF (verified by MRS) Xpert MTB/RIF, inpatient or outpatient (2 studies, tuberculosis prevalence 1% and 4%): sensitivity was 43% and 100% (16 participants; very low-certainty evidence) and specificity was 99% and 100% (771 participants; moderate-certainty evidence). Of 1000 children, where 50 have pulmonary tuberculosis, 31 to 69 would be Xpert MTB/RIF-positive, of whom 9 to 19 (28% to 29%) would not have pulmonary tuberculosis; 969 to 931 would be Xpert MTB/RIF-negative, of whom 0 to 28 (0% to 3%) would have tuberculosis. Studies often assessed more symptoms than those included in the index test and symptom definitions varied. These differences complicated data aggregation and may have influenced accuracy estimates. Both symptoms and CXR formed part of the CRS (incorporation bias), which may have led to overestimation of sensitivity and specificity.

AUTHORS' CONCLUSIONS

We found that in children who are tuberculosis contacts or living with HIV, screening tests using symptoms or CXR may be useful, but our review is limited by design issues with the index test and incorporation bias in the reference standard. For Xpert MTB/RIF, we found insufficient evidence regarding screening accuracy. Prospective evaluations of screening tests for tuberculosis in children will help clarify their use. In the meantime, screening strategies need to be pragmatic to address the persistent gaps in prevention and case detection that exist in resource-limited settings.

Design and Evaluation of Risk Assessment Tools to Identify Pediatric Tuberculosis Infection in Bohol, the Philippines, a Low-HIV- and High-TB-Burden Setting

Identifying children with, or at substantial risk of, Mycobacterium tuberculosis infection (TBI) and providing TB preventive therapy (TPT) represent an important, yet challenging, strategy in curbing the global burden of childhood TB. Risk assessment scoring tools, which quantify risks associated with unique factors characterizing an individual, could act as a surrogate measure of TBI risk and guide effective and efficient TPT delivery. We assessed important risk factors of childhood TBI and created risk assessment tools through secondary analysis of data from a large, community-based childhood TB prevalence study in the island province of Bohol in the Philippines, a low–HIV- and high–TB-burden, post-disaster setting. We identified four factors that were statistically associated with acquiring TBI—being 5 years or older, having a known TB contact, having a known TB contact who was either the mother or another primary caregiver, and living in a high–TB-burden municipality. We created 2-item, 4-item, and 9-item scores intended to identify child TBI in this low-resource, low–HIV-, and high–TB-burden setting. In addition to the design, evaluation, and impact analysis of these generalizable and valuable risk assessment tools, our study findings emphasize the necessity of targeting both household and community-associated transmissions of childhood TBI to achieve the global goal to end TB.

Geospatial and hot spot analysis of paediatric tuberculosis infection in Bohol, Philippines

Tuberculosis (TB) in children is a critical public health issue. In Bohol, Philippines, we found a high tuberculin skin test (TST)-positive prevalence (weighted prevalence = 6.4%) among 5476 children (<15 years) from 184 villages, with geographically isolated communities having prevalence as high as 29%. Therefore, we conducted a geospatial and hot spot analysis to examine the association between villages with high TST-positive prevalence (⩾6.5%) and access to medical care (distance (in kilometres and minutes of travel time) to the municipal Rural Health Units (RHU)), access to healthcare resources (distance to Provincial Health Office (PHO)) and socioeconomic determinants of health. Hot spot analysis revealed significant clusters of TST-positive prevalence in villages farthest from the PHO. Based on univariate analysis, the following variables associated with high prevalence were included in the multivariate model: minutes of travel time to the PHO, distance to the PHO, island villages and total deprivation based on socioeconomic indicators. In the final model, only distance to PHO in minutes was significant (P = 0.005). When evaluated further, greater than 1-hour drive significantly increased risk for TST-positivity (P = 0.003). Distance to healthcare resources likely increases the risk of TB transmission within the community. Expanding TB control efforts to geographically isolated areas is critical.