Causes of severe pneumonia requiring hospital admission in children without HIV infection from Africa and Asia: the PERCH multi-country case-control study

Pneumonia Etiology Research for Child Health (PERCH) Study Group, Katherine L O'Brien, Henry C Baggett, W Abdullah Brooks, Daniel R Feikin, Laura L Hammitt, Melissa M Higdon, Stephen R C Howie, Maria Deloria Knoll, Karen L Kotloff, Orin S Levine, Shabir A Madhi, David R Murdoch, Christine Prosperi, J Anthony G Scott, Qiyuan Shi, Donald M Thea, Zhenke Wu, Scott L Zeger, Peter V Adrian, Pasakorn Akarasewi, Trevor P Anderson, Martin Antonio, Juliet O Awori, Vicky L Baillie, Charatdao Bunthi, James Chipeta, Mohammod Jobayer Chisti, Jane Crawley, Andrea N DeLuca, Amanda J Driscoll, Bernard E Ebruke, Hubert P Endtz, Nicholas Fancourt, Wei Fu, Doli Goswami, Michelle J Groome, Meredith Haddix, Lokman Hossain, Yasmin Jahan, E Wangeci Kagucia, Alice Kamau, Ruth A Karron, Sidi Kazungu, Nana Kourouma, Locadiah Kuwanda, Geoffrey Kwenda, Mengying Li, Eunice M Machuka, Grant Mackenzie, Nasreen Mahomed, Susan A Maloney, Jessica L McLellan, Joanne L Mitchell, David P Moore, Susan C Morpeth, Azwifarwi Mudau, Lawrence Mwananyanda, James Mwansa, Micah Silaba Ominde, Uma Onwuchekwa, Daniel E Park, Julia Rhodes, Pongpun Sawatwong, Phil Seidenberg, Arifin Shamsul, Eric A F Simões, Seydou Sissoko, Somwe Wa Somwe, Samba O Sow, Mamadou Sylla, Boubou Tamboura, Milagritos D Tapia, Somsak Thamthitiwat, Aliou Toure, Nora L Watson, Khalequ Zaman, Syed M A Zaman, Pneumonia Etiology Research for Child Health (PERCH) Study Group, Katherine L O'Brien, Henry C Baggett, W Abdullah Brooks, Daniel R Feikin, Laura L Hammitt, Melissa M Higdon, Stephen R C Howie, Maria Deloria Knoll, Karen L Kotloff, Orin S Levine, Shabir A Madhi, David R Murdoch, Christine Prosperi, J Anthony G Scott, Qiyuan Shi, Donald M Thea, Zhenke Wu, Scott L Zeger, Peter V Adrian, Pasakorn Akarasewi, Trevor P Anderson, Martin Antonio, Juliet O Awori, Vicky L Baillie, Charatdao Bunthi, James Chipeta, Mohammod Jobayer Chisti, Jane Crawley, Andrea N DeLuca, Amanda J Driscoll, Bernard E Ebruke, Hubert P Endtz, Nicholas Fancourt, Wei Fu, Doli Goswami, Michelle J Groome, Meredith Haddix, Lokman Hossain, Yasmin Jahan, E Wangeci Kagucia, Alice Kamau, Ruth A Karron, Sidi Kazungu, Nana Kourouma, Locadiah Kuwanda, Geoffrey Kwenda, Mengying Li, Eunice M Machuka, Grant Mackenzie, Nasreen Mahomed, Susan A Maloney, Jessica L McLellan, Joanne L Mitchell, David P Moore, Susan C Morpeth, Azwifarwi Mudau, Lawrence Mwananyanda, James Mwansa, Micah Silaba Ominde, Uma Onwuchekwa, Daniel E Park, Julia Rhodes, Pongpun Sawatwong, Phil Seidenberg, Arifin Shamsul, Eric A F Simões, Seydou Sissoko, Somwe Wa Somwe, Samba O Sow, Mamadou Sylla, Boubou Tamboura, Milagritos D Tapia, Somsak Thamthitiwat, Aliou Toure, Nora L Watson, Khalequ Zaman, Syed M A Zaman

Abstract

Background: Pneumonia is the leading cause of death among children younger than 5 years. In this study, we estimated causes of pneumonia in young African and Asian children, using novel analytical methods applied to clinical and microbiological findings.

Methods: We did a multi-site, international case-control study in nine study sites in seven countries: Bangladesh, The Gambia, Kenya, Mali, South Africa, Thailand, and Zambia. All sites enrolled in the study for 24 months. Cases were children aged 1-59 months admitted to hospital with severe pneumonia. Controls were age-group-matched children randomly selected from communities surrounding study sites. Nasopharyngeal and oropharyngeal (NP-OP), urine, blood, induced sputum, lung aspirate, pleural fluid, and gastric aspirates were tested with cultures, multiplex PCR, or both. Primary analyses were restricted to cases without HIV infection and with abnormal chest x-rays and to controls without HIV infection. We applied a Bayesian, partial latent class analysis to estimate probabilities of aetiological agents at the individual and population level, incorporating case and control data.

Findings: Between Aug 15, 2011, and Jan 30, 2014, we enrolled 4232 cases and 5119 community controls. The primary analysis group was comprised of 1769 (41·8% of 4232) cases without HIV infection and with positive chest x-rays and 5102 (99·7% of 5119) community controls without HIV infection. Wheezing was present in 555 (31·7%) of 1752 cases (range by site 10·6-97·3%). 30-day case-fatality ratio was 6·4% (114 of 1769 cases). Blood cultures were positive in 56 (3·2%) of 1749 cases, and Streptococcus pneumoniae was the most common bacteria isolated (19 [33·9%] of 56). Almost all cases (98·9%) and controls (98·0%) had at least one pathogen detected by PCR in the NP-OP specimen. The detection of respiratory syncytial virus (RSV), parainfluenza virus, human metapneumovirus, influenza virus, S pneumoniae, Haemophilus influenzae type b (Hib), H influenzae non-type b, and Pneumocystis jirovecii in NP-OP specimens was associated with case status. The aetiology analysis estimated that viruses accounted for 61·4% (95% credible interval [CrI] 57·3-65·6) of causes, whereas bacteria accounted for 27·3% (23·3-31·6) and Mycobacterium tuberculosis for 5·9% (3·9-8·3). Viruses were less common (54·5%, 95% CrI 47·4-61·5 vs 68·0%, 62·7-72·7) and bacteria more common (33·7%, 27·2-40·8 vs 22·8%, 18·3-27·6) in very severe pneumonia cases than in severe cases. RSV had the greatest aetiological fraction (31·1%, 95% CrI 28·4-34·2) of all pathogens. Human rhinovirus, human metapneumovirus A or B, human parainfluenza virus, S pneumoniae, M tuberculosis, and H influenzae each accounted for 5% or more of the aetiological distribution. We observed differences in aetiological fraction by age for Bordetella pertussis, parainfluenza types 1 and 3, parechovirus-enterovirus, P jirovecii, RSV, rhinovirus, Staphylococcus aureus, and S pneumoniae, and differences by severity for RSV, S aureus, S pneumoniae, and parainfluenza type 3. The leading ten pathogens of each site accounted for 79% or more of the site's aetiological fraction.

Interpretation: In our study, a small set of pathogens accounted for most cases of pneumonia requiring hospital admission. Preventing and treating a subset of pathogens could substantially affect childhood pneumonia outcomes.

Funding: Bill & Melinda Gates Foundation.

Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Figures

Figure 1
Figure 1
Case (A) and control (B) enrolment and specimen availability profile CXR=chest x-ray. NP=nasopharyngeal. OP=oropharyngeal. WB=whole blood. LA=lung aspirate. PF=pleural fluid. IS=induced sputum. GA=gastric aspirate. *Of the 88 children not enrolled because of other reasons, 45 were not enrolled because of an enrolment cap at the Mali site, ten because of political unrest in Bangladesh, and 24 in Kenya and nine in Zambia because of reasons not stated. †Included in clinical descriptive analysis. ‡Lung aspirate and pleural fluid specimens were collected on a subset of cases eligible for the procedures; for samples with low volumes, only culture was done. §Measles testing was done on a subset of cases who met the study defined clinical criteria for measles. ¶Included in laboratory descriptive analysis and aetiology analysis; at least one of the following specimens was required for a child to be included in the aetiology analysis: blood culture, NP-OP PCR, WB PCR, or tuberculosis culture for cases; and NP-OP PCR or WB PCR for controls. ||Number contacted, screened, and eligible includes some extrapolated data for the Zambia and South Africa sites; data were available for 16 of 24 months for Zambia and 10·5 of 24 months for South Africa; for each of these sites, available data were used to extrapolate numbers for the months with missing data assuming that contact, participation, and eligibility rates were constant over time.**Not shown here are an additional 206 controls with HIV infection enrolled from HIV clinics at the South Africa and Zambia sites to ensure adequate sample size of children with HIV infection; these children will be described in forthcoming manuscripts devoted to the causes of severe and very severe pneumonia in children with HIV infection. ††Data for total number of children contacted and number of children who declined or did not show to clinic were not available for the Mali site. ‡‡Among sites with available data for total number of children contacted (ie, all sites except Mali), 8149 (73·9%) of 11 033 randomly selected children or households were contacted; the number of children or guardians contacted is used as the denominator for the percentage of children screened, eligible, and enrolled; because the denominator excludes Mali but the numerator does not, the percentages for screened, eligible, and enrolled are overestimated.
Figure 2
Figure 2
Blood culture results by study site in cases with positive chest x-ray and without HIV infection Enterobacteriaceae includes Escherichia coli, Enterobacter spp, and Klebsiella spp, excluding mixed Gram-negative rods. Other streptopcocci and enterococci include Streptococcus pyogenes and Enterococcus faecium. Mixed label includes Salmonella spp and other streptopcocci and enterococci. Contaminants, including those organisms deemed to be contaminants after clinical review, were excluded from the analysis. Figure is restricted to cases with available blood culture results. The numbers on the top of the bars refer to the total number of positive blood cultures. Two of the cases positive for pneumococcus in Kenya were pneumococcal conjugate vaccine (PCV) 13-type but not PCV10-type (serotypes 19A and 6A). Antibiotic pretreatment (defined as having a positive serum bioassay result, antibiotics administered at the referral facility, or antibiotic administration before whole-blood specimen collection at the study facility) varied by site: The Gambia (composite 10·6%, bioassay 7·6%), Mali (22·4%, 17·1%), Kenya (35·1%, 10·0%), Zambia (92·2%, 25·3%), South Africa (57·2%, 54·2%), Bangladesh (24·6%, 21·6%), and Thailand (30·6%, 19·4%).
Figure 3
Figure 3
Nasopharyngeal-oropharyngeal (NP-OP) pathogen prevalence* and adjusted odds ratios (OR) in cases with positive chest x-ray and without HIV infection and in controls without HIV infection Pathogens are ordered alphabetically among bacteria, followed by viruses and fungi. ORs adjusted for age (months), site, and presence of other pathogens detected by NP-OP PCR, but not adjusted for previous antibiotic use, which is known to influence bacterial positivity. *Prevalence defined by use of NP-OP PCR density thresholds for four pathogens: Pneumocystis jirovecii, 4 log10 copies per mL; Haemophilus influenzae, 5·9 log10 copies per mL; cytomegalovirus, 4·9 log10 copies per mL; Streptococcus pneumoniae, 6·9 log10 copies per mL; NP-OP PCR results based on positivity are in the appendix. PCV=pneumococcal conjugate vaccine.
Figure 4
Figure 4
Aetiological fraction unstratified (A), stratified by age (B), and stratified by severity (C) for cases with a positive chest x-ray and without HIV infection from all PERCH sites combined Lines represent 95% credible interval; the darker region of the line represents the IQR. The size of the symbol is scaled on the basis of the ratio of the estimated aetiological fraction to its SE. Of two identical aetiological fraction estimates, the estimate associated with a larger symbol is more informed by the data than the priors. Positive chest x-rays defined as consolidation or other infiltrate on the x-ray. The following pathogens contributed less than 1% to the aetiological fraction (overall and after stratifying by age and severity) and were excluded from the figure: Coronavirus, Chlamydophila pneumoniae, and Mycoplasma pneumoniae. Other streptococci and enterococci includes Streptococcus pyogenes and Enterococcus faecium. Non-fermentative Gram-negative rods (NFGNR) includes Acinetobacter spp and Pseudomonas spp. Enterobacteriaceae includes Escherichia coli, Enterobacter spp, and Klebsiella spp, excluding mixed Gram-negative rods. Pathogens that were estimated at the subspecies level, but grouped to the species level for display include parainfluenza virus type 1, 2, 3 and 4; Streptococcus pneumoniae PCV 13 and S pneumoniae non-PCV 13 types; Haemophilus influenzae type b and H influenzae non-type b; and influenza A, B, and C. Exact figures, including subspecies and serotype disaggregation (eg, PCV13 type and non-PCV13 type), are given in the appendix. NOS=not otherwise specified (ie, pathogens we did not test for).
Figure 5
Figure 5
Site-specific aetiology results for ten focus pathogens in cases with a positive chest x-ray and without HIV infection The size of the symbol is scaled on the basis of the ratio of the estimated aetiological fraction to its SE. Of two identical aetiological fraction estimates, the estimate associated with a larger symbol is more informed by the data than the priors. Positive chest x-rays defined as consolidation or other infiltrate on the x-ray. Graph restricted to the ten focus pathogens from the all-site analysis, which include those with aetiology estimate higher than 5% (n=7) or higher than 2% that were of epidemiological interest (defined as treatable by antibiotics [Pneumocystis jirovecii and Staphylococcus aureus] or having an available vaccine [influenza virus]). The 95% credibility intervals for the aetiological fractions of these three pathogens overlap with some non-focus pathogens, hence our use of the term focus pathogen rather than labelling these ten as the most common pathogens. Other pathogens category represents the sum of the aetiological fraction for all remaining pathogens tested for, but not presented in this figure. Site-specific results were standardised to the following case mix: 40% younger than 1 year with severe pneumonia, 20% younger than 1 year with very severe pneumonia, 30% aged 1 year or older with severe pneumonia, and 10% aged 1 year or older with very severe pneumonia. Pathogens estimated at the subspecies level, but grouped to the species level for display include parainfluenza virus types 1, 2, 3, and 4; Streptococcus pneumoniae PCV13 and S pneumoniae non-PCV13 types; Haemophilus influenzae type b and H influenzae non-type b; and influenza virus A, B, and C. Exact figures are given in the appendix. NOS=not otherwise specified (ie, pathogens we did not test for). *The summary for bacteria excludes Mycobacterium tuberculosis.
Figure 6
Figure 6
Cumulative contribution of site-specific ten most common pathogens in cases with a positive chest x-ray and without HIV infection Positive chest x-rays defined as consolidation or other infiltrate on the x-ray. Site-specific results were standardised to the following case mix: 40% younger than 1 year with severe pneumonia, 20% younger than 1 year with very severe pneumonia, 30% aged 1 year or older with severe pneumonia, and 10% aged 1 year or older with very severe pneumonia. Ranks correspond to the site-specific rank from the top ten pathogens of each site; the pathogen corresponding to each rank varies by site (see inset panel). Other strep category includes Streptococcus pyogenes and Enterococcus faecium. Non-fermentative Gram-negative rods (NFGNR) includes Acinetobacter spp and Pseudomonas spp. Enterobacteriaceae category (Entrb) includes Escherichia coli, Enterobacteriaceae spp, and Klebsiella spp, excluding mixed Gram-negative rods. Pathogens estimated at the subspecies level, but grouped to the species level for display include parainfluenza virus types 1, 2, 3, and 4; Streptococcus pneumoniae PCV13 and S pneumoniae non-PCV13 types; Haemophilus influenzae type b and H influenzae non-type b; and influenza virus A, B, and C. Boca=human bocavirus. Cand sp=Candida spp. CMV=cytomegalovirus. Flu=influenza virus A, B and C. H inf=H influenzae. HMPV=human metapneumovirus A or B. Mtb=Mycobacterium tuberculosis. M cat=Moraxella catarrhalis. NOS=not otherwise specified (ie, pathogens we did not test for). P jirov=Pneumocystis jirovecii. Para=parainfluenza virus type 1, 2, 3 and 4. PV-EV=parechovirus–enterovirus. Rhino=human rhinovirus. RSV=respiratory syncytial virus A or B. S aur=Staphylococcus aureus. S pneu=S pneumoniae. Salm sp=Salmonella spp.

References

    1. Liu L, Oza S, Hogan D. Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet. 2016;388:3027–3035.
    1. Feikin D, Flannery B, Hamel M, Stack M, Hansen P. Disease control priorities: reproductive, maternal, newborn, and child health. 3rd. World Bank; Washington DC: 2016. Vaccines for children in low- and middle-income countries; pp. 187–204.
    1. Lee LA, Franzel L, Atwell J. The estimated mortality impact of vaccinations forecast to be administered during 2011–2020 in 73 countries supported by the GAVI Alliance. Vaccine. 2013;31:B61–B72.
    1. Levine OS, O’Brien KL, Deloria-Knoll M. The Pneumonia Etiology Research for Child Health Project: a 21st century childhood pneumonia etiology study. Clin Infect Dis. 2012;54:S93–S101.
    1. Gilani Z, Kwong YD, Levine OS. A literature review and survey of childhood pneumonia etiology studies: 2000–2010. Clin Infect Dis. 2012;54(suppl 2):S102–S108.
    1. Feikin DR, Hammitt LL, Murdoch DR, O’Brien KL, Scott JAG. The enduring challenge of determining pneumonia etiology in children: considerations for future research priorities. Clin Infect Dis. 2017;64:S188–S196.
    1. Wu Z, Deloria-Knoll M, Hammitt LL, Zeger SL. Partially latent class models for case-control studies of childhood pneumonia aetiology. J R Stat Soc Ser C Appl Stat. 2016;65:97–114.
    1. Wu Z, Deloria-Knoll M, Zeger S. Nested partially-latent class models for dependent binary data; estimating disease etiology. Biostatistics. 2017;18:200–213.
    1. Deloria Knoll M, Fu W, Shi Q. Bayesian estimation of pneumonia etiology: epidemiologic considerations and applications to the Pneumonia Etiology Research for Child Health Study. Clin Infect Dis. 2017;64:S213–S227.
    1. Scott JAG, Wonodi C, Moïsi JC. The definition of pneumonia, the assessment of severity, and clinical standardization in the Pneumonia Etiology Research for Child Health study. Clin Infect Dis. 2012;54(suppl 2):S109–S116.
    1. Deloria-Knoll M, Feikin DR, Scott JAG. Identification and selection of cases and controls in the Pneumonia Etiology Research for Child Health Project. Clin Infect Dis. 2012;54:S117–S123.
    1. WHO Pocket book of hospital care for children: guidelines for the management of common illnesses with limited resources. 2005
    1. Higdon MM, Hammitt LL, Deloria Knoll M. Should controls with respiratory symptoms be excluded from case-control studies of pneumonia etiology? Reflections from the PERCH study. Clin Infect Dis. 2017;64:S205–S212.
    1. DeLuca AN, Regenberg A, Sugarman J, Murdoch DR, Levine O. Bioethical considerations in developing a biorepository for the Pneumonia Etiology Research for Child Health Project. Clin Infect Dis. 2012;54:S172–S179.
    1. Crawley J, Prosperi C, Baggett HC. Standardization of clinical assessment and sample collection across all PERCH study sites. Clin Infect Dis. 2017;64:S228–S237.
    1. Watson NL, Prosperi C, Driscoll AJ. Data management and data quality in PERCH, a large international case-control study of severe childhood pneumonia. Clin Infect Dis. 2017;64:S238–S244.
    1. Driscoll AJ, Karron RA, Morpeth SC. Standardization of laboratory methods for the PERCH study. Clin Infect Dis. 2017;64:S245–S252.
    1. The PERCH Study Group The Pneumonia Etiology Research for Child Health Project (PERCH) study materials. 2012
    1. Cherian T, Mulholland EK, Carlin JB. Standardized interpretation of paediatric chest radiographs for the diagnosis of pneumonia in epidemiological studies. Bull World Health Organ. 2005;83:353–359.
    1. Fancourt N, Deloria Knoll M, Barger-Kamate B. Standardized interpretation of chest radiographs in cases of pediatric pneumonia from the PERCH study. Clin Infect Dis. 2017;64:S253–S261.
    1. Fancourt N, Deloria-Knoll M, Baggett HC. Chest radiograph findings in childhood pneumonia cases from the multi-site PERCH study. Clin Infect Dis. 2017;64(suppl 3):S262–S270.
    1. Murdoch DR, O’Brien KL, Driscoll AJ, Karron RA, Bhat N. Laboratory methods for determining pneumonia etiology in children. Clin Infect Dis. 2012;54(suppl 2):S146–S152.
    1. Feikin DR, Fu W, Park DE. Is Higher viral load in the upper respiratory tract associated with severe pneumonia? Findings from the PERCH study. Clin Infect Dis. 2017;64:S337–S346.
    1. Park DE, Baggett HC, Howie SRC. Colonization density of the upper respiratory tract as a predictor of pneumonia—Haemophilus influenzae, Moraxella catarrhalis, Staphylococcus aureus, and Pneumocystis jirovecii. Clin Infect Dis. 2017;64:S328–S336.
    1. Baggett HC, Watson NL, Deloria Knoll M. Density of upper respiratory colonization with Streptococcus pneumoniae and its role in the diagnosis of pneumococcal pneumonia among children aged <5 years in the PERCH study. Clin Infect Dis. 2017;64:S317–S327.
    1. Morpeth SC, Deloria Knoll M, Scott JAG. Detection of pneumococcal DNA in blood by polymerase chain reaction for diagnosing pneumococcal pneumonia in young children from low- and middle-income countries. Clin Infect Dis. 2017;64:S347–S356.
    1. Deloria Knoll M, Morpeth SC, Scott JAG. Evaluation of pneumococcal load in blood by polymerase chain reaction for the diagnosis of pneumococcal pneumonia in young children in the PERCH study. Clin Infect Dis. 2017;64:S357–S367.
    1. Driscoll AJ, Deloria Knoll M, Hammitt LL. The effect of antibiotic exposure and specimen volume on the detection of bacterial pathogens in children with pneumonia. Clin Infect Dis. 2017;64:S368–S377.
    1. Zar HJ, Barnett W, Stadler A, Gardner-Lubbe S, Myer L, Nicol MP. Aetiology of childhood pneumonia in a well vaccinated South African birth cohort: a nested case-control study of the Drakenstein Child Health Study. Lancet Respir Med. 2016;4:463–472.
    1. Murdoch DR, Morpeth SC, Hammitt LL. Microscopic analysis and quality assessment of induced sputum from children with pneumonia in the PERCH study. Clin Infect Dis. 2017;64:S271–S279.
    1. Murdoch DR, Morpeth SC, Hammitt LL. The diagnostic utility of induced sputum microscopy and culture in childhood pneumonia. Clin Infect Dis. 2017;64:S280–S288.
    1. Thea DM, Seidenberg P, Park DE. Limited utility of polymerase chain reaction in induced sputum specimens for determining the causes of childhood pneumonia in resource-poor settings: findings from the Pneumonia Etiology Research for Child Health (PERCH) study. Clin Infect Dis. 2017;64:S289–S300.
    1. Turner P, Hinds J, Turner C. Improved detection of nasopharyngeal cocolonization by multiple pneumococcal serotypes by use of latex agglutination or molecular serotyping by microarray. J Clin Microbiol. 2011;49:1784–1789.
    1. WHO . World health Organization; Geneva: 1991. Technical bases for the WHO recommendations on the management of pneumonia in children at first-level health facilities: programme for the control of acute respiratory infections.
    1. Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin DB. 3rd. Taylor & Francis Group; Boca Raton, FL: 2014. Bayesian data analysis.
    1. Hammitt LL, Feikin DR, Scott JAG. Addressing the analytic challenges of cross-sectional pediatric pneumonia etiology data. Clin Infect Dis. 2017;64:S197–S204.
    1. WHO WHO AnthroPlus software. 2009
    1. Jain S, Williams DJ, Arnold SR. Community-acquired pneumonia requiring hospitalization among U.S. children. N Engl J Med. 2015;372:835–845.
    1. Bénet T, Picot VS, Awasthi S. Severity of pneumonia in under 5-year-old children from developing countries: a multicenter, prospective, observational study. Am J Trop Med Hyg. 2017;97:68–76.
    1. Tang JW, Lam TT, Zaraket H. Global epidemiology of non-influenza RNA respiratory viruses: data gaps and a growing need for surveillance. Lancet Infect Dis. 2017;17:e320–e326.
    1. Spichak TV, Yatsyshina SB, Katosova LK, Kim SS, Korppi MO. Is the role of rhinoviruses as causative agents of pediatric community-acquired pneumonia over-estimated? Eur J Pediatr. 2016;175:1951–1958.
    1. Pretorius MA, Tempia S, Walaza S. The role of influenza, RSV and other common respiratory viruses in severe acute respiratory infections and influenza-like illness in a population with a high HIV sero-prevalence, South Africa 2012–2015. J Clin Virol. 2016;75:21–26.
    1. Dagan R, Shriker O, Hazan I. Prospective study to determine clinical relevance of detection of pneumococcal DNA in sera of children by PCR. J Clin Microbiol. 1998;36:669–673.
    1. Dowell SF, Garman RL, Liu G, Levine OS, Yang YH. Evaluation of Binax NOW, an assay for the detection of pneumococcal antigen in urine samples, performed among pediatric patients. Clin Infect Dis. 2001;32:824–825.
    1. Johnson HL, Deloria-Knoll M, Levine OS. Systematic evaluation of serotypes causing invasive pneumococcal disease among children under five: the pneumococcal global serotype project. PLoS Med. 2010;7:e1000348.
    1. Cutts FT, Zaman SMA, Enwere G. Efficacy of nine-valent pneumococcal conjugate vaccine against pneumonia and invasive pneumococcal disease in The Gambia: randomised, double-blind, placebo-controlled trial. Lancet. 2005;365:1139–1146.
    1. Klugman KP, Madhi S a, Huebner R. A trial of a 9-valent pneumococcal conjugate vaccine in children with and those without HIV infection. N Engl J Med. 2003;349:1341–1348.
    1. Tregnaghi MW, Sáez-Llorens X, López P. Efficacy of pneumococcal nontypable Haemophilus influenzae protein D conjugate vaccine (PHiD-CV) in young Latin American children: a double-blind randomized controlled trial. PLoS Med. 2014;11:e1001657.
    1. Piralam B, Tomczyk SM, Rhodes JC. Incidence of pneumococcal pneumonia among adults in rural Thailand, 2006–2011: Implications for pneumococcal vaccine considerations. Am J Trop Med Hyg. 2015;93:1140–1147.
    1. Rhodes J, Dejsirilert S, Maloney SA. Pneumococcal bacteremia requiring hospitalization in rural Thailand: an update on incidence, clinical characteristics, serotype distribution, and antimicrobial susceptibility, 2005–2010. PLoS One. 2013;8:e66038.
    1. Baggett HC, Peruski LF, Olsen SJ. Incidence of pneumococcal bacteremia requiring hospitalization in rural Thailand. Clin Infect Dis. 2009;48:S65–S74.
    1. Moore DP, Higdon MM, Hammitt LL. The incremental value of repeated induced sputum and gastric aspirate samples for the diagnosis of pulmonary tuberculosis in young children with acute community-acquired pneumonia. Clin Infect Dis. 2017;64:S309–S316.
    1. Nicol MP, Zar HJ. New specimens and laboratory diagnostics for childhood pulmonary TB: progress and prospects. Paediatr Respir Rev. 2011;12:16–21.
    1. Barger-Kamate B, Deloria Knoll M, Kagucia EW. Pertussis-associated pneumonia in infants and children from low- and middle-income countries participating in the PERCH Study. Clin Infect Dis. 2016;63:S187–S196.
    1. Ideh RC, Howie SRC, Ebruke B. Transthoracic lung aspiration for the aetiological diagnosis of pneumonia: 25 years of experience from The Gambia. Int J Tuberc Lung Dis. 2011;15:729–735.
    1. Dawood FS, Fry AM, Goswami D. Incidence and characteristics of early childhood wheezing, Dhaka, Bangladesh, 2004–2010. Pediatr Pulmonol. 2016;51:588–595.
    1. Murray EL, Brondi L, Kleinbaum D. Cooking fuel type, household ventilation, and the risk of acute lower respiratory illness in urban Bangladeshi children: a longitudinal study. Indoor Air. 2012;22:132–139.
    1. Silk BJ, Cohen AL, Abedin J. Household air quality risk factors associated with childhood pneumonia in urban Dhaka, Bangladesh. Am J Trop Med Hyg. 2014;90:968–975.
    1. Ngari MM, Fegan G, Mwangome MK. Mortality after inpatient treatment for severe pneumonia in children: a cohort study. Paediatr Perinat Epidemiol. 2017;31:233–242.
    1. Kotloff KL, Nataro JP, Blackwelder WC. Burden and aetiology of diarrhoeal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case-control study. Lancet. 2013;382:209–222.
    1. Fry AM, Curns AT, Harbour K, Hutwagner L, Holman RC, Anderson LJ. Seasonal trends of human parainfluenza viral infections: United States, 1990–2004. Clin Infect Dis. 2006;43:1016–1022.
    1. Cox N. Influenza seasonality: timing and formulation of vaccines. Bull World Health Organ. 2014;92:311–411.
    1. Broutin H, Guégan J-F, Elguero E, Simondon F, Cazelles B. Large-scale comparative analysis of pertussis population dynamics: periodicity, synchrony, and impact of vaccination. Am J Epidemiol. 2005;161:1159–1167.
    1. Omori R, Nakata Y, Tessmer HL, Suzuki S, Shibayama K. The determinant of periodicity in Mycoplasma pneumoniae incidence: an insight from mathematical modelling. Sci Rep. 2015;5:14473.
    1. Bénet T, Sánchez Picot V, Messaoudi M. Microorganisms associated with pneumonia in children <5 years of age in developing and emerging countries: the GABRIEL pneumonia multicenter, prospective, case-control study. Clin Infect Dis. 2017;54:S93–S101.
    1. Selwyn BJ, Coordinated Data Group of BOSTID Researchers The epidemiology of acute respiratory tract infection in young children: comparison of findings from several developing countries. Rev Infect Dis. 1990;12:S870–S888.
    1. Bale JR. Creation of a research program to determine the etiology and epidemiology of acute respiratory tract infection among children in developing countries. Rev Infect Dis. 1990;12(suppl 8):S861–S866.
    1. Feikin D, Scott J, Gessner B. Use of vaccines as probes to define disease burden. Lancet. 2014;383:1762–1770.
    1. Saha SK, Schrag SJ, El Arifeen S. Causes and incidence of community-acquired serious infections among young children in south Asia (ANISA): an observational cohort study. Lancet. 2018;392:145–159.
    1. International Vaccine Access Center VIEW-hub: Data visualization platform.

Source: PubMed

3
Abonnieren