The score of integrated disease surveillance and response adequacy (SIA): a pragmatic score for comparing weekly reported diseases based on a systematic review.

BACKGROUND: The Integrated Disease Surveillance and Response (IDSR) strategy implemented by the World Health Organization (WHO) in Africa has produced a large amount of data on participating countries, and in particular on the Democratic Republic of Congo (DRC). These data are increasingly considered as unevaluable and, therefore, as requiring a rigorous process of validation before they can be used for research or public health purposes. The aim of this study was to propose a method to assess the level of adequacy of IDSR morbidity data in reflecting actual morbidity. METHODS: A systematic search of English- and French-language articles was performed in Scopus, Medline, Science Direct, Springer Link, Cochrane, Cairn, Persée, and Erudit databases. Other types of documents were identified through manual searches. Selected articles focused on the determinants of the discrepancies (differences) between reported morbidity and actual morbidity. An adequacy score was constructed using some of the identified determinants. This score was applied to the 15 weekly reported diseases monitored by IDSR surveillance in the DRC. A classification was established using the Jenks method and a sensitivity analysis was performed. Twenty-three classes of determinants were identified in 35 IDSR technical guides and reports of outbreak investigations and in 71 out of 2254 researched articles. For each of the 15 weekly reported diseases, the SIA was composed of 12 items grouped in 6 dimensions. RESULTS: The SIA classified the 15 weekly reported diseases into 3 categories or types: high score or good adequacy (value > = 14), moderate score or fair adequacy (value > = 8 and < 14), and low score or low or non-adequacy (value < 8). Regardless of the criteria used in the sensitivity analysis, there was no notable variation in SIA values or categories for any of the 15 weekly reported diseases. CONCLUSION: In a context of sparse health information in low- and middle-income countries, this study developed a score to help classify IDSR morbidity data as usable, usable after adjustment, or unusable. This score can serve to prioritize, optimize, and interpret data analyses for epidemiological research or public health purposes.

Temporal and Spatial Dynamics of Monkeypox in Democratic Republic of Congo, 2000-2015.

Monkeypox is a viral disease with a clinical presentation resembling that of smallpox. Although monkeypox is considered to be an important zoonotic viral disease, its epidemiology remains poorly understood, especially the spatial and temporal distribution of the disease. The present study examined weekly reports of monkeypox cases collected from 2000 to 2015 at the health zone scale in the Democratic Republic of Congo. SaTScan® was performed to identify spatial and temporal clusters of monkeypox cases. Significant primary spatial clusters were detected in the districts of Sankuru and Tshuapa. A centrifugal pattern was found, with significant primary spatial clusters extending over time from Sankuru and Tshuapa to several neighboring districts. Peaks of cases occurred from July to September for the 2000-2002 and 2003-2009 sub-periods and from January to March for the 2010-2015 sub-period. Despite the lack of additional data for confirmation, the increasing of monkeypox reported incidence was observed in the Democratic Republic of Congo during 2000-2015 period and this increase cannot be explain only by the improvements of surveillance systems. The detected spatial clusters were located in the dense rainforest of the Congo basin. The reasons for the excess incidence of monkeypox cases in the central region of the country are unknown, and the relative influence of ecological, environmental, and human factors on the mechanism of emergence of monkeypox has yet to be identified.