Summary of findings for the main analysis
| Proactive case detection of common childhood illnesses by CHWs compared with usual care for reducing mortality and morbidity and improving access to care in children under 5 years of age | ||||
| Participants: children under 5 years of age accessing primary health services in LMICs Settings: India (three studies), Mali (two studies), Bangladesh, Dominican Republic, Nepal, Pakistan, Senegal, South Africa Intervention: home visits by CHWs for proactive detection of common childhood illnesses Comparison: usual primary care (passive case detection) available from facilities and, in some cases, CHWs | ||||
| Outcomes | Relative risk | Number of studies | Certainty of the evidence (GRADE)* | Comments |
| Neonatal mortality Verbal reports Follow-up: 0–12 months | 0.43 to 1.07 | 3† |  Low‡§ | Two Indian studies found proactive case detection of newborn illnesses reduced mortality, although only the non-randomised evidence was statistically significant. Proactive case detection may reduce neonatalmortality. However effects vary, and it is possible that it makes littleor no difference to this outcome. |
| Infant mortality Verbal reports Follow-up: 0–36 months | 0.52 to 0.94 | 4¶ |  Low**†† | Four Southeast Asia studies found reductions in infant mortality, although not all were statistically significant. Two studies targeted various infant conditions, and two specifically targeted pneumonia among children under 5. Proactive case detection may reduce infantmortality. |
| Childmortality Verbal reports Follow-up: 0–84 months | 0.04 to 0.80 | 4‡‡ |  Very low††§§¶¶ | Four studies found important reductions in under-5 mortality, although three were uncontrolled before–after analyses. It is uncertain whether proactive case detectionreduces mortality among children under 5. |
| Prevalence of infectious diseases Verbal reports, diagnostic tests Follow-up: 0–24 months | 0.06 to 1.02 | 6*** |  Very low†††‡‡‡§§§¶¶¶ | Three West African studies found significant reductions in fever or malarial fever. One study found reductions in both newborn and infant illnesses. Two studies found no effect on child diarrhoea, a secondary intervention outcome. It is uncertain whether proactive case detectionreduces the prevalence of infectious diseases. |
| Prevalence of nutritional outcomes Athropometric measurement Follow-up: 0–24 months | 0.61 to 1.16 | 3**** |  Low§§§†††† | One study targeted childhood nutrition and found positive effects on length and BMI for age. Two studies that targeted various infant conditions found a range of nutritional effects. Proactive case detection may improve nutritional outcomes, although it is possible that it makes littleor no difference to this outcome. |
| Hospitalisation Verbal reports, hospital records Follow-up: 0–24 months | 0.38 to 1.26 | 4‡‡‡‡ |  Very low§§§††††§§§§¶¶¶¶ | Hospitalisation may reflect a higher severity of illness, improved treatment seeking, or both. In the two studies where CHWs provided doorstep treatment, hospitalisation significantly declined. In the two studies where all cases detected by CHWs were referred, hospitalisation increased, although results were not statistically significant. It is uncertain whether proactive case detectionreduces hospitalisation. |
| Access to effective treatment Verbal reports Follow-up: 0–24 months | 1.59 to 4.64 | 2***** |  Low§§§,††††,††††† | One study found that treatment was sought more often from an appropriate provider for neonatal illness and infection, and infant diarrhoea and pneumonia. One childhood nutritional intervention improved administration of ORS during diarrhoea. Proactive case detection may increase access to effective treatment. |
| Access to prompt treatment Verbal reports Follow-up: 0–84 months | 1.00 to 2.39 | 3‡‡‡‡‡ |  Very low§.§§§,§§§§§,¶¶¶¶¶ | One study found a significant improvement in the speed of treatment for newborns, but no effect for infants with diarrhoea and pneumonia. Uncontrolled before–after analyses in Mali found that the risk of prompt antimalarial treatment among children more than doubled. It is uncertain whether proactive case detectionimproves access to prompt treatment. |
High: this research provides a very good indication of the likely effect. The likelihood that the effect will be substantially different‡ is low.
Moderate: this research provides a good indication of the likely effect. The likelihood that the effect will be substantially different‡ is moderate.
Low: this research provides some indication of the likely effect. However, the likelihood that it will be substantially different‡ is high.
Very low: this research does not provide a reliable indication of the likely effect. The likelihood that the effect will be substantially different‡ is very high.
‡Substantially different=a large enough difference that it might affect a decision.
*GRADE, Working Group grades of evidence.
†Bang 1999, Bhandari 2012, Tomlinson 2014.
‡The quality of evidence was downgraded for indirectness as the interventions in Bang 1999 and Bhandari 2012 included components other than proactive case detection, and comparison CHWs in Tomlinson 2014 conducted home visits for other purposes.
§The 95% CIs included both no effect and appreciable benefit.
¶Bang 1999, Bhandari 2012, Khan 1990, Pandey 1991.
**Risk of bias was assessed as low for Bang 1999 and Bhandari 2012. Khan 1990 and Pandey 1991 employed inappropriate analytical methods for their study designs. The quality of evidence was therefore downgraded for this limitation.
††The quality of evidence was downgraded for indirectness as the interventions in all studies included components other than proactive case detection, such as removal of user fees, facility-level capacity building, and/or women’s education.
‡‡Johnson 2013, Johnson 2018, Khan 1990, Pandey 1991.
§§The quality of evidence was downgraded for risk of bias in Johnson 2013 and 2018 (shape of preintervention period not established and no control area for comparison) and in Khan 1990 and Pandey 1991 (inappropriate analyses for study designs).
¶¶The quality of evidence was downgraded for important inconsistency in results; many of the 95% CIs were not overlapping. Heterogeneity may be explained by differences in follow-up times (up to 84 months in Johnson 2018) and/or diseases targeted (only respiratory infection in Khan 1990 and Pandey 1991).
***Johnson 2013, Johnson 2018, Linn 2015, Mazumder 2014, Navarro 2013, Tomlinson 2014.
†††The quality of evidence was downgraded for limitations in design in Johnson 2013 and 2018 (shape of preintervention period not established and no control area for comparison), Navarro 2013 (outcome assessors not blind; high loss to follow-up and differences between lost and retained participants) and Linn 2015 (outcome assessors not blind; potential confounders not controlled for in analysis).
‡‡‡The quality of evidence was downgraded for important inconsistency in results. However, in the studies that showed a significant reduction in prevalence, the intervention targeted the diseases assessed for this outcome; in Navarro 2013 and Tomlinson 2014, CHWs conducted proactive case detection and management of conditions (nutritional and newborn, respectively) other than those assessed for this outcome.
§§§The quality of evidence was downgraded for indirectness due to cointerventions and differences in age groups.
¶¶¶The quality of evidence was upgraded for very large effects found in Linn 2015; weak study design may not explain all of the observed effect.
****Mazumder 2014, Navarro 2013, Tomlinson 2014.
††††Risk of bias assessed as low for Mazumder 2014, unclear for Tomlinson 2014 (no baseline measurement of outcomes; unclear risk of contamination), and high for Navarro 2013 (outcome assessors not blind; high loss to follow-up and differences between lost and retained participants).
‡‡‡‡Chen 1980, Mazumder 2014, Navarro 2013, Tomlinson 2014. In Chen 1980, the intervention targeted and was assessed for the entire population; results not reported in such a way that the outcome could be calculated separately for children under 5.
§§§§Chen 1980 is a non-randomised trial with suggestion of important baseline imbalances in outcomes and confounding factors, although no statistical comparisons made at baseline. The quality of evidence was therefore downgraded for limitations in design.
¶¶¶¶Serious inconsistency in results, although likely due to whether CHWs provided doorstep treatment (likely to reduce hospitalisation), or referral only (likely to increase hospitalisation). The quality of evidence was therefore not downgraded for inconsistency, but for imprecision due to very wide 95% CIs.
*****Mazumder 2014, Navarro 2013.
†††††The quality of evidence was downgraded for imprecision as studies had very wide 95% CIs.
‡‡‡‡‡Johnson 2013, Johnson 2018, Mazumder 2014.
§§§§§Risk of bias was assessed as low for Mazumder 2014, but high for Johnson 2013 and 2018 (shape of preintervention period not established and no control area for comparison). The quality of evidence was therefore downgraded for this limitation in design.
¶¶¶¶¶The quality of evidence was downgraded for important inconsistency in results; however, it may be explained by differences in intervention, target populations and follow-up times.
BMI, body mass index ; CHWs, community health worker; GRADE, Grading of Recommendations, Assessment, Development and Evaluation; LMICs, low-income and middle-income countries; ORS, oral rehydration solution.
