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

Assessment of the integrated disease surveillance and response system implementation in health zones at risk for viral hemorrhagic fever outbreaks in North Kivu, Democratic Republic of the Congo, following a major Ebola outbreak, 2021

BACKGROUND

The Democratic Republic of the Congo (DRC) experienced its largest Ebola Virus Disease Outbreak in 2018-2020. As a result of the outbreak, significant funding and international support were provided to Eastern DRC to improve disease surveillance. The Integrated Disease Surveillance and Response (IDSR) strategy has been used in the DRC as a framework to strengthen public health surveillance, and full implementation could be critical as the DRC continues to face threats of various epidemic-prone diseases. In 2021, the DRC initiated an IDSR assessment in North Kivu province to assess the capabilities of the public health system to detect and respond to new public health threats.

METHODS

The study utilized a mixed-methods design consisting of quantitative and qualitative methods. Quantitative assessment of the performance in IDSR core functions was conducted at multiple levels of the tiered health system through a standardized questionnaire and analysis of health data. Qualitative data were also collected through observations, focus groups and open-ended questions. Data were collected at the North Kivu provincial public health office, five health zones, 66 healthcare facilities, and from community health workers in 15 health areas.

RESULTS

Thirty-six percent of health facilities had no case definition documents and 53% had no blank case reporting forms, limiting identification and reporting. Data completeness and timeliness among health facilities were 53% and 75% overall but varied widely by health zone. While these indicators seemingly improved at the health zone level at 100% and 97% respectively, the health facility data feeding into the reporting structure were inconsistent. The use of electronic Integrated Disease Surveillance and Response is not widely implemented. Rapid response teams were generally available, but functionality was low with lack of guidance documents and long response times.

CONCLUSION

Support is needed at the lower levels of the public health system and to address specific zones with low performance. Limitations in materials, resources for communication and transportation, and workforce training continue to be challenges. This assessment highlights the need to move from outbreak-focused support and funding to building systems that can improve the long-term functionality of the routine disease surveillance system.

Spatiotemporal dynamics of cholera hotspots in the Democratic Republic of the Congo from 1973 to 2022

BACKGROUND

Since the early 1970s, cholera outbreaks have been a major public health burden in the Democratic Republic of Congo (DRC). Cholera cases have been reported in a quasi-continuous manner in certain lakeside areas in the Great Lakes Region. As these cholera-endemic health zones constitute a starting point for outbreaks and diffusion towards other at-risk areas, they play a major role in cholera dynamics in the country. Monitoring the spatiotemporal dynamics of cholera hotspots and adjusting interventions accordingly thus reduces the disease burden in an efficient and cost-effective manner.

METHODS

A literature review was conducted to describe the spatiotemporal dynamics of cholera in the DRC at the province level from 1973 to 1999. We then identified and classified cholera hotspots at the provincial and health zone levels from 2003 to 2022 and described the spatiotemporal evolution of hotspots. We also applied and compared three different classification methods to ensure that cholera hotspots are identified and classified according to the DRC context.

RESULTS

According to all three methods, high-priority hotspots were concentrated in the eastern Great Lakes Region. Overall, hotspots largely remained unchanged over the course of the study period, although slight improvements were observed in some eastern hotspots, while other non-endemic areas in the west experienced an increase in cholera outbreaks. The Global Task Force on Cholera Control (GTFCC) and the Department of Ecology and Infectious Disease Control (DEIDC) methods largely yielded similar results for the high-risk hotspots. However, the medium-priority hotspots identified by the GTFCC method were further sub-classified by the DEIDC method, thereby providing a more detailed ranking for priority targeting.

CONCLUSIONS

Overall, the findings of this comprehensive study shed light on the dynamics of cholera hotspots in the DRC from 1973 to 2022. These results may serve as an evidence-based foundation for public health officials and policymakers to improve the implementation of the Multisectoral Cholera Elimination Plan, guiding targeted interventions and resource allocation to mitigate the impact of cholera in vulnerable communities.

Spatiotemporal dynamics of cholera in the Democratic Republic of the Congo before and during the implementation of the Multisectoral Cholera Elimination Plan: a cross-sectional study from 2000 to 2021

BACKGROUND

The Democratic Republic of the Congo (DRC) implemented the first strategic Multisectoral Cholera Elimination Plan (MCEP) in 2008-2012. Two subsequent MCEPs have since been implemented covering the periods 2013-2017 and 2018-2021. The current study aimed to assess the spatiotemporal dynamics of cholera over the recent 22-year period to determine the impact of the MCEPs on cholera epidemics, establish lessons learned and provide an evidence-based foundation to improve the implementation of the next MCEP (2023-2027).

METHODS

In this cross-sectional study, secondary weekly epidemiological cholera data covering the 2000-2021 period was extracted from the DRC Ministry of Health surveillance databases. The data series was divided into four periods: pre-MCEP 2003-2007 (pre-MCEP), first MCEP (MCEP-1), second MCEP (MCEP-2) and third MCEP (MCEP-3). For each period, we assessed the overall cholera profiles and seasonal patterns. We analyzed the spatial dynamics and identified cholera risk clusters at the province level. We also assessed the evolution of cholera sanctuary zones identified during each period.

RESULTS

During the 2000-2021 period, the DRC recorded 520,024 suspected cases and 12,561 deaths. The endemic provinces remain the most affected with more than 75% of cases, five of the six endemic provinces were identified as risk clusters during each MCEP period (North Kivu, South Kivu, Tanganyika, Haut-Lomami and Haut-Katanga). Several health zones were identified as cholera sanctuary zones during the study period: 14 health zones during MCEP-1, 14 health zones during MCEP-2 and 29 health zones during MCEP-3. Over the course of the study period, seasonal cholera patterns remained constant, with one peak during the dry season and one peak during the rainy season.

CONCLUSION

Despite the implementation of three MCEPs, the cholera context in the DRC remains largely unchanged since the pre-MCEP period. To better orient cholera elimination activities, the method used to classify priority health zones should be optimized by analyzing epidemiological; water, sanitation and hygiene; socio-economic; environmental and health indicators at the local level. Improvements should also be made regarding the implementation of the MCEP, reporting of funded activities and surveillance of cholera cases. Additional studies should aim to identify specific bottlenecks and gaps in the coordination and strategic efforts of cholera elimination interventions at the local, national and international levels.

Drivers of the dynamics of the spread of cholera in the Democratic Republic of the Congo, 2000-2018: An eco-epidemiological study

BACKGROUND

The dynamics of the spread of cholera epidemics in the Democratic Republic of the Congo (DRC), from east to west and within western DRC, have been extensively studied. However, the drivers of these spread processes remain unclear. We therefore sought to better understand the factors associated with these spread dynamics and their potential underlying mechanisms.

METHODS

In this eco-epidemiological study, we focused on the spread processes of cholera epidemics originating from the shores of Lake Kivu, involving the areas bordering Lake Kivu, the areas surrounding the lake areas, and the areas out of endemic eastern DRC (eastern and western non-endemic provinces). Over the period 2000-2018, we collected data on suspected cholera cases, and a set of several variables including types of conflicts, the number of internally displaced persons (IDPs), population density, transportation network density, and accessibility indicators. Using multivariate ordinal logistic regression models, we identified factors associated with the spread of cholera outside the endemic eastern DRC. We performed multivariate Vector Auto Regressive models to analyze potential underlying mechanisms involving the factors associated with these spread dynamics. Finally, we classified the affected health zones using hierarchical ascendant classification based on principal component analysis (PCA).

FINDINGS

The increase in the number of suspected cholera cases, the exacerbation of conflict events, and the number of IDPs in eastern endemic areas were associated with an increased risk of cholera spreading outside the endemic eastern provinces. We found that the increase in suspected cholera cases was influenced by the increase in battles at lag of 4 weeks, which were influenced by the violence against civilians with a 1-week lag. The violent conflict events influenced the increase in the number of IDPs 4 to 6 weeks later. Other influences and uni- or bidirectional causal links were observed between violent and non-violent conflicts, and between conflicts and IDPs. Hierarchical clustering on PCA identified three categories of affected health zones: densely populated urban areas with few but large and longer epidemics; moderately and accessible areas with more but small epidemics; less populated and less accessible areas with more and larger epidemics.

CONCLUSION

Our findings argue for monitoring conflict dynamics to predict the risk of geographic expansion of cholera in the DRC. They also suggest areas where interventions should be appropriately focused to build their resilience to the disease.

Modalities and preferred routes of geographic spread of cholera from endemic areas in eastern Democratic Republic of the Congo

Cholera is endemic along the Great Lakes Region, in eastern Democratic Republic of the Congo (DRC). From these endemic areas, also under perpetual conflicts, outbreaks spread to other areas. However, the main routes of propagation remain unclear. This research aimed to explore the modalities and likely main routes of geographic spread of cholera from endemic areas in eastern DRC. We used historical reconstruction of major outbreak expansions of cholera since its introduction in eastern DRC, maps of distribution and spatiotemporal cluster detection analyses of cholera data from passive surveillance (2000–2017) to describe the spread dynamics of cholera from eastern DRC. Four modalities of geographic spread and their likely main routes from the source areas of epidemics to other areas were identified: in endemic eastern provinces, and in non-endemic provinces of eastern, central and western DRC. Using non-parametric statistics, we found that the higher the number of conflict events reported in eastern DRC, the greater the geographic spread of cholera across the country. The present study revealed that the dynamics of the spread of cholera follow a fairly well-defined spatial logic and can therefore be predicted.

The spread of cholera in western Democratic Republic of the Congo is not unidirectional from East-West: a spatiotemporal analysis, 1973-2018

BACKGROUND

Cholera outbreaks in western Democratic Republic of the Congo (DRC) are thought to be primarily the result of westward spread of cases from the Great Lakes Region. However, other patterns of spatial spread in this part of the country should not be excluded. The aim of this study was to explore alternative routes of spatial spread in western DRC.

METHODS

A literature review was conducted to reconstruct major outbreak expansions of cholera in western DRC since its introduction in 1973. We also collected data on cholera cases reported at the health zone (HZ) scale by the national surveillance system during 2000-2018. Based on data from routine disease surveillance, we identified two subperiods (week 45, 2012-week 42, 2013 and week 40, 2017-week 52, 2018) for which the retrospective space-time permutation scan statistic was implemented to detect spatiotemporal clusters of cholera cases and then to infer the spread patterns in western DRC other than that described in the literature.

RESULTS

Beyond westward and cross-border spread in the West Congo Basin from the Great Lakes Region, other dynamics of cholera epidemic propagation were observed from neighboring countries, such as Angola, to non-endemic provinces of southwestern DRC. Space-time clustering analyses sequentially detected clusters of cholera cases from southwestern DRC to the northern provinces, demonstrating a downstream-to-upstream spread along the Congo River.

CONCLUSIONS

The spread of cholera in western DRC is not one-sided. There are other patterns of spatial spread, including a propagation from downstream to upstream areas along the Congo River, to be considered as preferential trajectories of cholera in western DRC.

Twenty years of integrated disease surveillance and response in Sub-Saharan Africa: challenges and opportunities for effective management of infectious disease epidemics

INTRODUCTION

This systematic review aimed to analyse the performance of the Integrated Disease Surveillance and Response (IDSR) strategy in Sub-Saharan Africa (SSA) and how its implementation has embraced advancement in information technology, big data analytics techniques and wealth of data sources.

METHODS

HINARI, PubMed, and advanced Google Scholar databases were searched for eligible articles. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols.

RESULTS

A total of 1,809 articles were identified and screened at two stages. Forty-five studies met the inclusion criteria, of which 35 were country-specific, seven covered the SSA region, and three covered 3-4 countries. Twenty-six studies assessed the IDSR core functions, 43 the support functions, while 24 addressed both functions. Most of the studies involved Tanzania (9), Ghana (6) and Uganda (5). The routine Health Management Information System (HMIS), which collects data from health care facilities, has remained the primary source of IDSR data. However, the system is characterised by inadequate data completeness, timeliness, quality, analysis and utilisation, and lack of integration of data from other sources. Under-use of advanced and big data analytical technologies in performing disease surveillance and relating multiple indicators minimises the optimisation of clinical and practice evidence-based decision-making.

CONCLUSIONS

This review indicates that most countries in SSA rely mainly on traditional indicator-based disease surveillance utilising data from healthcare facilities with limited use of data from other sources. It is high time that SSA countries consider and adopt multi-sectoral, multi-disease and multi-indicator platforms that integrate other sources of health information to provide support to effective detection and prompt response to public health threats.

The environmental drivers of bacterial meningitis epidemics in the Democratic Republic of Congo, central Africa

INTRODUCTION

Bacterial meningitis still constitutes an important threat in Africa. In the meningitis belt, a clear seasonal pattern in the incidence of meningococcal disease during the dry season has been previously correlated with several environmental parameters like dust and sand particles as well as the Harmattan winds. In parallel, the evidence of seasonality in meningitis dynamics and its environmental variables remain poorly studied outside the meningitis belt. This study explores several environmental factors associated with meningitis cases in the Democratic Republic of Congo (DRC), central Africa, outside the meningitis belt area.

METHODS

Non-parametric Kruskal-Wallis' tests were used to establish the difference between the different health zones, climate and vegetation types in relation to both the number of cases and attack rates for the period 2000-2018. The relationships between the number of meningitis cases for the different health zones and environmental and socio-economical parameters collected were modeled using different generalized linear (GLMs) and generalized linear mixed models (GLMMs), and different error structure in the different models, i.e., Poisson, binomial negative, zero-inflated binomial negative and more elaborated multi-hierarchical zero-inflated binomial negative models, with randomization of certain parameters or factors (health zones, vegetation and climate types). Comparing the different statistical models, the model with the smallest Akaike's information criterion (AIC) were selected as the best ones. 515 different health zones from 26 distinct provinces were considered for the construction of the different GLM and GLMM models.

RESULTS

Non-parametric bivariate statistics showed that there were more meningitis cases in urban health zones than in rural conditions (χ2 = 6.910, p-value = 0.009), in areas dominated by savannah landscape than in areas with dense forest or forest in mountainous areas (χ2 = 15.185, p-value = 0.001), and with no significant difference between climate types (χ2 = 1.211, p-value = 0,449). Additionally, no significant difference was observed for attack rate between the two types of heath zones (χ2 = 0.982, p-value = 0.322). Conversely, strong differences in attack rate values were obtained for vegetation types (χ2 = 13.627, p-value = 0,001) and climate types (χ2 = 13.627, p-value = 0,001). This work demonstrates that, all other parameters kept constant, an urban health zone located at high latitude and longitude eastwards, located at low-altitude like in valley ecosystems predominantly covered by savannah biome, with a humid tropical climate are at higher risk for the development of meningitis. In addition, the regions with mean range temperature and a population with a low index of economic well-being (IEW) constitute the perfect conditions for the development of meningitis in DRC.

CONCLUSION

In a context of global environmental change, particularly climate change, our findings tend to show that an interplay of different environmental and socio-economic drivers are important to consider in the epidemiology of bacterial meningitis epidemics in DRC. This information is important to help improving meningitis control strategies in a large country located outside of the so-called meningitis belt.

Profile of communicable diseases reported under integrated disease surveillance programme from a teaching hospital

Background:

Integrated disease surveillance programme (IDSP) maintains laboratory-based disease surveillance system for epidemic prone diseases in our country. This study was undertaken to analyze the epidemiological profile and seasonal variations of various communicable diseases reported to IDSP over a 5-year period from 2014 to 2018 from our institute.

Methods:

All laboratory confirmed communicable diseases reported under IDSP over a 5-year period were analyzed for their distribution with respect to epidemiological variables, geographical distribution, and seasonal variation.

Statistical Analysis:

Data was entered in MS excel sheet and the results expressed as percentages.

Results:

A total of 3,602 communicable diseases were reported under IDSP during the time period from January 2014 to December 2018. Dengue continues to be the most common reported disease over the years followed by Scrub typhus which had an outbreak in 2018. Furthermore, adult males in the productive age group of 21–30 years are commonly affected by almost all communicable diseases. Seasonal variation was noted in communicable diseases with highest number of cases in the rainy season of October to December in Puducherry as well as a peak in January and June.

Conclusions:

The pattern of communicable diseases that have been diagnosed and reported will prove to be useful in planning appropriate preventive and containment measures in the near future as well as in creating awareness in the community.