Despite significant investment in early outbreak detection, there is very little evidence with respect to factors that influence earlier detection. More research is needed to guide intervention planning.

A literature review was conducted to assess the burden of serious fungal infections in the Democratic Republic of the Congo (DRC) (population 95,326,000). English and French publications were listed and analysed using PubMed/Medline, Google Scholar and the African Journals database. Publication dates spanning 1943–2020 were included in the scope of the review. From the analysis of published articles, we estimate a total of about 5,177,000 people (5.4%) suffer from serious fungal infections in the DRC annually. The incidence of cryptococcal meningitis, Pneumocystis jirovecii pneumonia in adults and invasive aspergillosis in AIDS patients was estimated at 6168, 2800 and 380 cases per year. Oral and oesophageal candidiasis represent 50,470 and 28,800 HIV‐infected patients respectively. Chronic pulmonary aspergillosis post‐tuberculosis incidence and prevalence was estimated to be 54,700. Fungal asthma (allergic bronchopulmonary aspergillosis and severe asthma with fungal sensitization) probably has a prevalence of 88,800 and 117,200. The estimated prevalence of recurrent vulvovaginal candidiasis and tinea capitis is 1,202,640 and 3,551,900 respectively.Further work is required to provide additional studies on opportunistic infections for improving diagnosis and the implementation of a national surveillance programme of fungal disease in the DRC.

No abstract

Infectious disease outbreaks can have significant impact on individual health, national economies, and social well-being. Through early detection of an infectious disease, the outbreak can be contained at the local level, thereby reducing adverse effects on populations. Significant time and funding have been invested to improve disease detection timeliness. However, current evaluation methods do not provide evidencebased suggestions or measurements on how to detect outbreaks earlier. Key conditions for earlier detection and their influencing factors remain unclear and unmeasured. Without clarity about conditions and influencing factors, attempts to improve disease detection remain ad hoc and unsystematic. Methods: We developed a generic five-step disease detection model and a novel methodology to use for data collection, analysis, and interpretation. Data was collected in two workshops in Southeast Europe (n = 33 participants) and Southern and East Africa (n = 19 participants), representing mid-and low-income countries. Through systematic, qualitative, and quantitative data analyses, we identified key conditions for earlier detection and prioritized factors that influence them. As participants joined a workshop format and not an experimental setting, no ethics approval was required. Findings: Our analyses suggest that governance is the most important condition for earlier detection in both regions. Facilitating factors for earlier detection are risk communication activities such as information sharing, communication, and collaboration activities. Impeding factors are lack of communication, coordination, and leadership. Interpretation: Governance and risk communication are key influencers for earlier detection in both regions. However, inadequate technical capacity, commonly assumed to be a leading factor impeding early outbreak detection, was not found a leading factor. This insight may be used to pinpoint further improvement strategies.

No abstract