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Background: Pharmaceutical companies, regulatory agencies, or other government agencies conduct safety signal detection as one of the ways for mitigating the possible risks due to medical products. The safety signal is defined as information that arises from one or multiple sources (including observations or experiments), suggesting a new, potentially causal association, or a new aspect of a known association between an intervention like administration of a medicine and an event or set of related events, either adverse or beneficial, that is judged to be of sufficient likelihood to justify verificatory action. Definition of signal in this paper is restricted for pharmacovigilance to adverse events. Signal detection as a pharmacovigilance activity is highly recommended in the United States of America and it is mandatory in Europe. However, at the moment, the same cannot be said for any African country. Findings: Traditional techniques for signal detection work well when the adverse drug reaction reports are few and manageable to enable manual review. The data mining algorithms for signal detection perform well with large and/or pooled drug safety monitoring reports. The methods discussed are proportional reporting ratio (PRR), the Report Odds Ratio (ROR), the Bayesian Confidence Propagation Neural Network (BCPNN) and the Multi-item Gamma Poisson Shrinker (MGPS). These sophisticated methods are routinely used in developed countries at the moment. Conclusion: Data mining algorithms for signal detection need to be adopted in developing countries because the increased use of pharmaceutical products has led to exponential increase in safety reports and datasets.

Background: Pharmaceutical companies, regulatory agencies, or other government agencies conduct safety signal detection as one of the ways for mitigating the possible risks due to medical products. The safety signal is defined as information that arises from one or multiple sources (including observations or experiments), suggesting a new, potentially causal association, or a new aspect of a known association between an intervention like administration of a medicine and an event or set of related events, either adverse or beneficial, that is judged to be of sufficient likelihood to justify verificatory action. Definition of signal in this paper is restricted for pharmacovigilance to adverse events. Signal detection as a pharmacovigilance activity is highly recommended in the United States of America and it is mandatory in Europe. However, at the moment, the same cannot be said for any African country. Findings: Traditional techniques for signal detection work well when the adverse drug reaction reports are few and manageable to enable manual review. The data mining algorithms for signal detection perform well with large and/or pooled drug safety monitoring reports. The methods discussed are proportional reporting ratio (PRR), the Report Odds Ratio (ROR), the Bayesian Confidence Propagation Neural Network (BCPNN) and the Multi-item Gamma Poisson Shrinker (MGPS). These sophisticated methods are routinely used in developed countries at the moment. Conclusion: Data mining algorithms for signal detection need to be adopted in developing countries because the increased use of pharmaceutical products has led to exponential increase in safety reports and datasets.

Background: Many studies have assessed the level of bed net coverage in populations at risk of malaria infection. These revealed large variations in bed net use across countries, regions and social strata. Such studies are often aimed at identifying populations with low access to bed nets that should be prioritized in future interventions. However, often spatial differences in malaria endemicity are not taken into account. By ignoring variability in malaria endemicity, these studies prioritize populations with little access to bed nets, even if these happen to live in low endemicity areas. Conversely, populations living in regions with high malaria endemicity will receive a lower priority once a seizable proportion is protected by bed nets. Adequately assigning priorities requires accounting for both the current level of bed net coverage and the local malaria endemicity. Indeed, as shown here for 23 African countries, there is no correlation between the level of bed net coverage and the level of malaria endemicity in a region. Therefore, the need for future interventions can not be assessed based on current bed net coverage alone. This paper proposes the Adjusted Bed net Coverage (ABC) statistic as a measure taking into account both local malaria endemicity and the level of bed net coverage. The measure allows setting priorities for future interventions taking into account both local malaria endemicity and bed net coverage. Methods. A mathematical formulation of the ABC as a weighted difference of bed net coverage and malaria endemicity is presented. The formulation is parameterized based on a model of malaria epidemiology (Smith et al. Trends Parasitol 25:511-516, 2009). By parameterizing the ABC based on this model, the ABC as used in this paper is proxy for the steady-state malaria burden given the current level of bed net coverage. Data on the bed net coverage in under five year olds and malaria endemicity in 23 Sub-Saharan countries is used to show that the ABC prioritizes different populations than the level of bed net coverage by itself. Data from the following countries was used: Angola, Burkina Faso, Burundi, Cameroon, Congo Democratic Republic, Ethiopia, Ghana, Guinea, Kenya, Liberia, Madagascar, Malawi, Mali, Mozambique, Namibia, Nigeria, Rwanda, Senegal, Sierra Leone, Tanzania, Uganda, Zambia and Zimbabwe. The priority order given by the ABC and the bed net coverage are compared at the countries' level, the first level administrative divisions and for five different wealth quintiles. Results: Both at national level and at the level of the administrative divisions the ABC suggests a different priority order for selecting countries and divisions for future interventions. When taking into account malaria endemicity, measures assessing equality in access to bed nets across wealth quintiles, such as slopes of inequality, are prone to change. This suggests that when assessing inequality in access to bed nets one should take into account the local malaria endemicity for populations from different wealth quintiles. Conclusion: Accounting for malaria endemicity highlights different countries, regions and socio-economic strata for future intervention than the bed net coverage by itself. Therefore, care should be taken to factor out any effects of local malaria endemicity in assessing bed net coverage and in prioritizing populations for further scale-up of bed net coverage. The ABC is proposed as a simple means to do this that is derived from an existing model of malaria epidemiology. © 2013 Vanderelst and Speybroeck; licensee BioMed Central Ltd.

Background: Many studies have assessed the level of bed net coverage in populations at risk of malaria infection. These revealed large variations in bed net use across countries, regions and social strata. Such studies are often aimed at identifying populations with low access to bed nets that should be prioritized in future interventions. However, often spatial differences in malaria endemicity are not taken into account. By ignoring variability in malaria endemicity, these studies prioritize populations with little access to bed nets, even if these happen to live in low endemicity areas. Conversely, populations living in regions with high malaria endemicity will receive a lower priority once a seizable proportion is protected by bed nets. Adequately assigning priorities requires accounting for both the current level of bed net coverage and the local malaria endemicity. Indeed, as shown here for 23 African countries, there is no correlation between the level of bed net coverage and the level of malaria endemicity in a region. Therefore, the need for future interventions can not be assessed based on current bed net coverage alone. This paper proposes the Adjusted Bed net Coverage (ABC) statistic as a measure taking into account both local malaria endemicity and the level of bed net coverage. The measure allows setting priorities for future interventions taking into account both local malaria endemicity and bed net coverage. Methods. A mathematical formulation of the ABC as a weighted difference of bed net coverage and malaria endemicity is presented. The formulation is parameterized based on a model of malaria epidemiology (Smith et al. Trends Parasitol 25:511-516, 2009). By parameterizing the ABC based on this model, the ABC as used in this paper is proxy for the steady-state malaria burden given the current level of bed net coverage. Data on the bed net coverage in under five year olds and malaria endemicity in 23 Sub-Saharan countries is used to show that the ABC prioritizes different populations than the level of bed net coverage by itself. Data from the following countries was used: Angola, Burkina Faso, Burundi, Cameroon, Congo Democratic Republic, Ethiopia, Ghana, Guinea, Kenya, Liberia, Madagascar, Malawi, Mali, Mozambique, Namibia, Nigeria, Rwanda, Senegal, Sierra Leone, Tanzania, Uganda, Zambia and Zimbabwe. The priority order given by the ABC and the bed net coverage are compared at the countries' level, the first level administrative divisions and for five different wealth quintiles. Results: Both at national level and at the level of the administrative divisions the ABC suggests a different priority order for selecting countries and divisions for future interventions. When taking into account malaria endemicity, measures assessing equality in access to bed nets across wealth quintiles, such as slopes of inequality, are prone to change. This suggests that when assessing inequality in access to bed nets one should take into account the local malaria endemicity for populations from different wealth quintiles. Conclusion: Accounting for malaria endemicity highlights different countries, regions and socio-economic strata for future intervention than the bed net coverage by itself. Therefore, care should be taken to factor out any effects of local malaria endemicity in assessing bed net coverage and in prioritizing populations for further scale-up of bed net coverage. The ABC is proposed as a simple means to do this that is derived from an existing model of malaria epidemiology. © 2013 Vanderelst and Speybroeck; licensee BioMed Central Ltd.

Abstract Schistosomiasis is a poverty-related parasitic infection, leading to chronic ill-health. For more than a century, schistosomiasis has been known to be endemic in certain provinces of the Democratic Republic of Congo (DRC). However, a clear overview on the status of the disease within the country is currently lacking, which is seriously hampering control. Here, we review the available information on schistosomiasis in DRC of the past 60 years. Findings and data gaps are discussed in the perspective of upcoming control activities. An electronic literature search via PubMed complemented by manual search of non-peer-reviewed articles was conducted up to January 2015. The search concerned all relevant records related to schistosomiasis in the DRC from January 1955 onwards. A total of 155 records were found, of which 30 met the inclusion criteria. Results were summarized by geographical region, mapped, and compared with those reported sixty years ago. The available data reported schistosomiasis in some areas located in 10 of the 11 provinces of DRC. Three species of Schistosoma were found: S. mansoni , S. haematobium and S. intercalatum . The prevalence of schistosomiasis varied greatly between regions and between villages, with high values of up to 95 % observed in some communities. The overall trend over 60 years points to the spread of schistosomiasis to formerly non-endemic areas. The prevalence of schistosomiasis has increased in rural endemic areas and decreased in urban/peri-urban endemic areas of Kinshasa. Hepatosplenomegaly, urinary tract lesions and anaemia were commonly reported in schistosomiasis endemic areas but not always associated with infection status. The present review confirms that schistosomiasis is still endemic in DRC. However, available data are scattered across time and space and studies lack methodological uniformity, hampering a reliable estimation of the current status of schistosomiasis in DRC. There is a clear need for updated prevalence data and well-designed studies on the epidemiology and transmission of schistosomiasis in DRC. This will aid the national control program to adequately design and implement strategies for sustainable and comprehensive control of schistosomiasis throughout the country.

Schistosomiasis is a poverty-related parasitic infection, leading to chronic ill-health. For more than a century, schistosomiasis has been known to be endemic in certain provinces of the Democratic Republic of Congo (DRC). However, a clear overview on the status of the disease within the country is currently lacking, which is seriously hampering control. Here, we review the available information on schistosomiasis in DRC of the past 60 years. Findings and data gaps are discussed in the perspective of upcoming control activities.An electronic literature search via PubMed complemented by manual search of non-peer-reviewed articles was conducted up to January 2015. The search concerned all relevant records related to schistosomiasis in the DRC from January 1955 onwards. A total of 155 records were found, of which 30 met the inclusion criteria. Results were summarized by geographical region, mapped, and compared with those reported sixty years ago. The available data reported schistosomiasis in some areas located in 10 of the 11 provinces of DRC. Three species of Schistosoma were found: S. mansoni, S. haematobium and S. intercalatum. The prevalence of schistosomiasis varied greatly between regions and between villages, with high values of up to 95 % observed in some communities. The overall trend over 60 years points to the spread of schistosomiasis to formerly non-endemic areas. The prevalence of schistosomiasis has increased in rural endemic areas and decreased in urban/peri-urban endemic areas of Kinshasa. Hepatosplenomegaly, urinary tract lesions and anaemia were commonly reported in schistosomiasis endemic areas but not always associated with infection status.The present review confirms that schistosomiasis is still endemic in DRC. However, available data are scattered across time and space and studies lack methodological uniformity, hampering a reliable estimation of the current status of schistosomiasis in DRC. There is a clear need for updated prevalence data and well-designed studies on the epidemiology and transmission of schistosomiasis in DRC. This will aid the national control program to adequately design and implement strategies for sustainable and comprehensive control of schistosomiasis throughout the country.

Schistosomiasis is a poverty-related parasitic infection, leading to chronic ill-health. For more than a century, schistosomiasis has been known to be endemic in certain provinces of the Democratic Republic of Congo (DRC). However, a clear overview on the status of the disease within the country is currently lacking, which is seriously hampering control. Here, we review the available information on schistosomiasis in DRC of the past 60 years. Findings and data gaps are discussed in the perspective of upcoming control activities.An electronic literature search via PubMed complemented by manual search of non-peer-reviewed articles was conducted up to January 2015. The search concerned all relevant records related to schistosomiasis in the DRC from January 1955 onwards. A total of 155 records were found, of which 30 met the inclusion criteria. Results were summarized by geographical region, mapped, and compared with those reported sixty years ago. The available data reported schistosomiasis in some areas located in 10 of the 11 provinces of DRC. Three species of Schistosoma were found: S. mansoni, S. haematobium and S. intercalatum. The prevalence of schistosomiasis varied greatly between regions and between villages, with high values of up to 95 % observed in some communities. The overall trend over 60 years points to the spread of schistosomiasis to formerly non-endemic areas. The prevalence of schistosomiasis has increased in rural endemic areas and decreased in urban/peri-urban endemic areas of Kinshasa. Hepatosplenomegaly, urinary tract lesions and anaemia were commonly reported in schistosomiasis endemic areas but not always associated with infection status.The present review confirms that schistosomiasis is still endemic in DRC. However, available data are scattered across time and space and studies lack methodological uniformity, hampering a reliable estimation of the current status of schistosomiasis in DRC. There is a clear need for updated prevalence data and well-designed studies on the epidemiology and transmission of schistosomiasis in DRC. This will aid the national control program to adequately design and implement strategies for sustainable and comprehensive control of schistosomiasis throughout the country.

Artemisinin-based combination therapies (ACTs) have been recommended by the World Health Organization (WHO) as first-line treatment of uncomplicated Plasmodium falciparum (P. falciparum) malaria since 2005 in Democratic Republic of Congo (DRC) and a regular surveillance of the ACT efficacy is required to ensure the treatment effectiveness. Mutations in the propeller domain of the pfk13 gene were identified as molecular markers of artemisinin resistance (ART-R). This study investigated the pfk13-propeller gene polymorphism in clinical isolates of P. falciparum collected in the DRC. In 2017, ten geographical sites across DRC were selected for a cross-sectional study that was conducted first in Kinshasa from January to March, then in the nine other sites from September to December. Dried blood samples were collected from patients attending health centers for fever where diagnosis of Malaria was first made by rapid diagnostic test (RDT) available on site (SD Bioline malaria Ag Pf or CareStart Malaria Pf) or by thick blood smear and then confirmed by a P. falciparum real-time PCR assay. A pfk13-propeller segment containing a fragment that codes for amino acids at positions 427-595 was amplified by conventional PCR before sequencing. In total, 1070 patients were enrolled in the study. Real-time PCR performed confirmed the initial diagnosis of P. falciparum infection in 806 samples (75.3%; 95% CI: 72.6%- 77.9%). Of the 717 successfully sequenced P. falciparum isolates, 710 (99.0%; 95% CI: 97.9% - 99.6) were wild-type genotypes and 7 (1.0%; 95% CI: 0.4% - 2.1%) carried non-synonymous (NS) mutations in pfk13-propeller including 2 mutations (A578S and V534A) previously detected and 2 other (M472I and A569T) not yet detected in the DRC. Mutations associated with ART-R in Southeast Asia were not observed in DRC. However, the presence of other mutations in pfk13-propeller gene calls for further investigations to assess their implication in drug resistance. ; Peer reviewed

Background: Taenia solium, a zoonotic parasite that is endemic in most developing countries where pork is consumed, is recognised as the main cause of acquired epilepsy in these regions. T. solium has been reported in almost all of the neighboring countries of Democratic Republic of Congo (DRC) but data on the current prevalence of the disease in the country itself are lacking. This study, focusing on porcine cysticercosis (CC), makes part of a first initiative to assess whether cysticercosis is indeed actually present in DRC. Methods: An epidemiological study on porcine CC was conducted (1) on urban markets of Kinshasa where pork is sold and (2) in villages in Bas-Congo province where pigs are traditionally reared. Tongue inspection and ELISA for the detection of circulating antigen of the larval stage of T. solium were used to assess the prevalence of active CC in both study sites. Findings: The overall prevalence of pigs with active cysticercosis did not significantly differ between the market and the village study sites (38.8 [CI95%: 34-43] versus 41.2% [CI95%: 33-49], respectively). However, tongue cysticercosis was only found in the village study site together with a significantly higher intensity of infection (detected by ELISA). Interpretation: Pigs reared at village level are sold for consumption on Kinshasa markets, but it seems that highly infected animals are excluded at a certain level in the pig trade chain. Indeed, preliminary informal surveys on common practices conducted in parallel revealed that pig farmers and/or buyers select the low infected animals and exclude those who are positive by tongue inspection at village level. This study provides the only recent evidence of CC presence in DRC and gives the first estimates to fill an important gap on the African taeniasis/cysticercosis distribution map.

Background: Taenia solium, a zoonotic parasite that is endemic in most developing countries where pork is consumed, is recognised as the main cause of acquired epilepsy in these regions. T. solium has been reported in almost all of the neighboring countries of Democratic Republic of Congo (DRC) but data on the current prevalence of the disease in the country itself are lacking. This study, focusing on porcine cysticercosis (CC), makes part of a first initiative to assess whether cysticercosis is indeed actually present in DRC. Methods: An epidemiological study on porcine CC was conducted (1) on urban markets of Kinshasa where pork is sold and (2) in villages in Bas-Congo province where pigs are traditionally reared. Tongue inspection and ELISA for the detection of circulating antigen of the larval stage of T. solium were used to assess the prevalence of active CC in both study sites. Findings: The overall prevalence of pigs with active cysticercosis did not significantly differ between the market and the village study sites (38.8 [CI95%: 34-43] versus 41.2% [CI95%: 33-49], respectively). However, tongue cysticercosis was only found in the village study site together with a significantly higher intensity of infection (detected by ELISA). Interpretation: Pigs reared at village level are sold for consumption on Kinshasa markets, but it seems that highly infected animals are excluded at a certain level in the pig trade chain. Indeed, preliminary informal surveys on common practices conducted in parallel revealed that pig farmers and/or buyers select the low infected animals and exclude those who are positive by tongue inspection at village level. This study provides the only recent evidence of CC presence in DRC and gives the first estimates to fill an important gap on the African taeniasis/cysticercosis distribution map.