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Background: Despite malaria, malnutrition and anaemia being major public-health challenges in Cameroon, very little has been reported on the interaction between these interconnected health determinants. This study therefore sought to investigate the relationship between malaria, anaemia, nutritional and socio-economic status amongst under—ten children living in six localities within two health districts in the North Region of Cameroon. Methods: Accordingly, a cross- sectional survey was conducted during the peak malaria season in November 2014, in Pitoa and Mayo-Oulo Health Districts. Three hundred and sixty eight children aged 6months—10 years were enrolled. Structured questionnaires were used to assess socio-economic status. Anthropometric indices were taken using standard methods and nutritional status assessed by calculating Height for Age (HA), Weight for Age (WA) and Weight for Height (WH) z-scores to determine stunting, underweight and wasting respectively. Finger-prick blood samples were used to prepare thin and thick blood smears for microscopy. Whole blood was collected to determine the PCV and blood spots on filter paper were used to extract plasmodium DNA for speciation by PCR. Results: Overall prevalence rates of malaria, malnutrition and anaemia were 32.9%, 54.1% and 20.6% respectively. Stunting, underweight and wasting were detected in 56.9%, 63.5% and 34.8% of the children respectively. There was a significant association between malaria and malnutrition [OR = 1.89, (95% CI: 1.12–3.19); (p = 0.017)]. Malnutrition was also strongly associated with malaria status [OR = 2.07, (95% CI: 1.22–3.53); (p = 0.007)]. The prevalence rates of mild, moderate and severe anaemia were 8.1%, 9.2% and 3.3% respectively. Both malaria status and anaemia correlated with development index [OR = 0.75, (95% CI: 0.58–0.99); (p = 0.042)] and [OR = 1.45, (95% CI: 1.05–2.00); (p = 0.023)] respectively. Conclusion: Our findings show a synergistic relationship between malaria and malnutrition. Effective collaboration between malaria control and nutrition intervention programmes is essential for proper case management and improved socio-economic status. [ABSTRACT FROM AUTHOR]

The end of the acute phase of the COVID-19 pandemic is near in some countries as declared by World Health Organization (WHO) in January 2022 based on some studies in Europe and South Africa despite unequal distribution of vaccines to combat the disease spread globally. The heterogeneity in individual age and the reaction to biological and environmental changes that has been observed in COVID-19 dynamics in terms of different reaction to vaccination by age group, severity of infection per age group, hospitalization and Intensive Care Unit (ICU) records show different patterns, and hence, it is important to improve mathematical models for COVID-19 pandemic prediction to account for different proportions of ages in the population, which is a major factor in epidemic history. We aim in this paper to estimate, using the Usher model, the lifespan loss due to viral infection and ageing which could result in pathological events such as infectious diseases. Exploiting epidemiology and demographic data firstly from Cameroon and then from some other countries, we described the ageing in the COVID-19 outbreak in human populations and performed a graphical representation of the proportion of sensitivity of some of the model parameters which we varied. The result shows a coherence between the orders of magnitude of the calculated and observed incidence numbers during the epidemic wave, which constitutes a semi-quantitative validation of the mathematical modelling approach at the population level. To conclude, the age heterogeneity of the populations involved in the COVID-19 outbreak needs the consideration of models in age groups with specific susceptibilities to infection. [ABSTRACT FROM AUTHOR]

Introduction: The role of age and sex in the presentation and outcome of endemic Burkitt lymphoma (BL) has not been studied recently. This study analysed these factors in 934 patients with BL who had received cyclophosphamide and intrathecal methotrexate as treatment. Methods: Records of 934 children diagnosed with BL from 2004 to 2015 were obtained from our Paediatric Oncology Networked Database (POND) cancer registry. Age at diagnosis, sex, disease stage, time to diagnosis, delay in diagnosis, completion of treatment, rate of abandonment, and one-year survival rates were recorded and statistically analysed. Results: The male to female ratio of 1.41 for the study population of 934. The median delay from onset of symptoms to diagnosis was 31 days. The St Jude stage distribution was I = 6.4%, II = 5.9%, III = 71.5% and IV = 16.2%. Significantly more patients presented with stage III disease in age groups 5–9 and 10–14 years than 0–4 years. The overall 1-year survival rate was 53.45%, respectively 77.1% for stage I, 67.9% for stage II, 55.1% for stage III and 32.4% for stage IV disease (p<0.001). There was no significant difference in survival by sex and age group. Conclusion: Patients aged under 5 years presented with less-advanced disease, but survival was not affected by age. Sex did not influence delay to diagnosis and overall survival. The long delay between the onset of symptoms and diagnosis emphasises the need for interventions to achieve an earlier diagnosis and a better survival rate. [ABSTRACT FROM AUTHOR]

Background: Malaria control efforts are highly skewed towards Plasmodium falciparum while overlooking other Plasmodium species such as P. malariae. A better understanding of the role of Plasmodium species other than P. falciparum is needed to strengthen malaria elimination initiatives. The aim of the present study was to elucidate the contribution of P. malariae to malaria transmission in Cameroon. Methods: The study was conducted in the Ngatti Health District, a forest–savannah transition area in the Adamawa Region, Cameroon. A total of 497 individuals aged from 1 to 85 years were diagnosed with malaria in November 2020 using a rapid diagnostic test (RDT) and microscopy. Adult mosquitoes were collected between September 2019 and March 2020 by indoor aspiration and identified morphologically and molecularly. The infection status of Plasmodium spp. was also determined by quantitative PCR, and dried blood spots were collected from 156 participants with the aim to detect different Plasmodium species by nested PCR. Results: The overall Plasmodium prevalence was 50.3%, 51.8% and 64.7%, as detected by microscopy, the RDT and PCR, respectively. Based on the PCR results, P. falciparum was the most prevalent species (43%); followed by co-infections P. falciparum/P. malariae (17%), P. falciparum/P. ovale (1.3%), P. falciparum/P. ovale/P. malariae (1.3%); and then by P. malariae mono-infection (2.5%). The same trend was observed using microscopy, with 35% of participants infected with P. falciparum, 11% co-infected with P. falciparum/P. malariae and 4% infected with P. malariae. The prevalence and parasite density of malaria infection varied significantly with age group (P < 0.05), with the highest prevalence rate observed in children aged 6–10 years (P = 0.0001) while the density of Plasmodium infection increased significantly in children aged < 5 years compared to the other age groups (P = 10−3). Among the 757 Anopheles mosquitoes collected, 737 (97.35%) were An. funestus sensu stricto, 15 (1.9%) were An. gambiae and 5 (0.6%) were An. hancocki. The Plasmodium species recorded at the head/thorax level were P. falciparum and P. malariae, with a sporozoite infection rate of 8.4%; the highest sporozoite infection rate was recorded at Mibellon village (13.6%). Conclusion: The results of this study reveal the significant contribution of P. malariae, in addition to P. falciparum, to the high malaria transmission rate in this region. These findings highlight the need to deploy initiatives to also tackle this Plasmodium species to eliminate malaria in the region. [ABSTRACT FROM AUTHOR]

Revisiting the classical model by Ross and Kermack-McKendrick, the Susceptible–Infectious–Recovered (SIR) model used to formalize the COVID-19 epidemic, requires improvements which will be the subject of this article. The heterogeneity in the age of the populations concerned leads to considering models in age groups with specific susceptibilities, which makes the prediction problem more difficult. Basically, there are three age groups of interest which are, respectively, 0–19 years, 20–64 years, and >64 years, but in this article, we only consider two (20–64 years and >64 years) age groups because the group 0–19 years is widely seen as being less infected by the virus since this age group had a low infection rate throughout the pandemic era of this study, especially the countries under consideration. In this article, we proposed a new mathematical age-dependent (Susceptible–Infectious–Goneanewsusceptible–Recovered (SIGR)) model for the COVID-19 outbreak and performed some mathematical analyses by showing the positivity, boundedness, stability, existence, and uniqueness of the solution. We performed numerical simulations of the model with parameters from Kuwait, France, and Cameroon. We discuss the role of these different parameters used in the model; namely, vaccination on the epidemic dynamics. We open a new perspective of improving an age-dependent model and its application to observed data and parameters. [ABSTRACT FROM AUTHOR]

In Cameroon, COVID-19 infection spread rapidly and nationwide, with up to 721 deaths reported. To the best of our knowledge, no study reported the on-theground data using a large patients' dataset to give a comprehensive knowledge on COVID-19 pandemic in Cameroon. The objective of this study was to shade lights on the epidemiological, virological and clinical features of COVID-19 in the Cameroonian context. An observational study was conducted among symptomatic and asymptomatic individuals tested for SARS-CoV-2 by PCR on nasopharyngeal samples from April 22nd, 2020 to January 5th, 2021. Out of 14119 individuals (59.8% male), overall SARS-CoV-2 positivity was 12.7% (from 7.9% in <10 years to 17.3% in >60 years, p<0.001). The positivity rate of symptomatic individuals was 36.1% versus 9.8% among asymptomatic ones, p<0.001. Age group =10 [aOR (95%CI): 0.515 (0.338-0.784), p=0.002] and being symptomatic [aOR (95% CI): 5.108 (4.521-5.771), p<0.001] were predictors of SARS-CoV-2 positivity. Regarding PCR Cycle Threshold (CT), 53.8% of positive individuals had a CT <30. According to age, compared to older individuals, those aged 21-40 years showed a higher proportion with high viraemia (CT<20; 21.3% versus 12.5% respectively, p=0.003). Similarly, symptomatic individuals showed a higher proportion with high viraemia (22.4%), when compared to asymptomatic (13.9%); p<0.001. During this first wave of the pandemic, overall SARS-CoV-2 positivity remained high (>10%) and was associated with the presence of symptoms and older age. Most of the infection is among young and asymptomatic individuals, suggesting the "track-and-test" strategy should target these potential transmitters. [ABSTRACT FROM AUTHOR]

Background: Increased risk of schistosomiasis in peri-urban and urban towns is not uncommon. An epidemiological survey was carried out in the Tiko Health District (THD), an unmapped transmission focus for urogenital schistosomiasis (UGS), to assess the distribution, intensity, and risk factors associated with the occurrence of UGS. Methods: In this cross-sectional survey, 12 communities were purposively selected from four health areas (HAs) (Likomba, Holforth, Holforth-Likomba, and Mutengene) in South West Region of Cameroon between June and August 2018. Consenting individuals were enrolled using a convenient sampling technique and administered a semi-structured questionnaire to document information on socio-demographic and water contact behaviour. Urine samples were examined for Schistosomahaematobium infection using test strip, filtration, and microscopy methods. Bivariate and binary logistic regression analyses were used to identify predictors of infection. Results: The overall prevalence of UGS in Likomba, Holforth-Likomba and Holforth was 31.5% [95% confidence interval (CI): 28.3–34.8] with geometric mean (GM) egg count of 28.7 (range: 2–450) eggs per 10 ml of urine. S.haematobium infection was not found in Mutengene HA. Infection was unevenly distributed among the HAs, Holforth-Likomba and Holforth being the most and least affected, respectively. The prevalence of infection varied (P < 0.001) among the affected communities, ranging from 12.0 to 56.9%. Infection status of the community related positively (P < 0.001) with proximity to stream (< 100 m), the degree of contact with water and number of improved water sources. Younger age group (5–14 years) [adjusted odds ratio (aOR): 3.7, 95% CI: 1.1–12.2] and intense water contact (degree II) (aOR: 5.2, 95% CI: 3.4–8.1) were associated with increased risk of infection. Similarly, significantly higher egg load was observed among younger aged groups (P = 0.02) and those who carried out intense water contact activities (P < 0.001). Conclusions: Generally, THD is a moderate risk endemic focus for UGS but prevalence higher than 50.0% was observed in some communities. These findings warrant immediate mass chemotherapy with praziquantel to reduce morbidity. Provision of portable water and health education are proposed measures to reduce and eventually eliminate transmission in the area. [ABSTRACT FROM AUTHOR]

Health disparities research in low- and middle-income countries (LMICs) is hampered by the difficulty of measuring economic status in low-resource settings. We previously developed the EconomicClusters k-medoids clustering-based algorithm for defining population-specific economic models based on few Demographic and Health Surveys (DHS) assets. The algorithm previously defined a twenty-group economic model for Cameroon. The aims of this study are to optimize the functionality of our EconomicClusters algorithm and app based on collaborator feedback from early use of this twenty-group economic model, to test the validity of the model as a metric of economic status, and to assess the utility of the model in another LMIC context. We condense the twenty Cameroonian economic groups into fewer, ordinally-ranked, groups using agglomerative hierarchical clustering based on mean cluster child height-for-age Z-score (HAZ), women’s literacy score, and proportion of children who are deceased. We develop an EconomicClusters model for Ghana consisting of five economic groups and rank these groups based on the same three variables. The proportion of variance in women’s literacy score accounted for by the EconomicClusters model was 5–12% less than the proportion of variance accounted for by the DHS Wealth Index model. The proportion of the variance in child HAZ and proportion of children who are deceased accounted for by the EconomicClusters model was similar to (0.4–2.5% less than) the proportion of variance accounted for by the DHS Wealth Index model. The EconomicClusters model requires asking only five questions, as opposed to greater than twenty Wealth Index questions. The EconomicClusters algorithm and app could facilitate health disparities research in any country with DHS data by generating ordinally-ranked, population-specific economic models that perform nearly as well as the Wealth Index in evaluating variability in health and social outcomes based on wealth status but that are more feasible to assess in time-constrained settings. [ABSTRACT FROM AUTHOR]

Background: Armed conflict is a significant social determinant of child health with nuanced effects. There is a dearth of knowledge on the public health issues facing vulnerable populations in conflict-stricken areas. The objective was to determine the prevalence and determinants of moderate to severe anaemia (MdSA) and severe stunting (SS) in children ≤3 years in conflict-hit Dibanda, Ekona and Muea in the Mount Cameroon area.Methods: Haematological parameters were obtained using an automated haematology analyser while undernutrition indices standard deviation (SD) scores (z- scores), were computed based on the WHO growth reference curves for 649 children in a community based cross-sectional study in 2018. Binomial logistic regression models were used to evaluate the determinants of MdSA and SS against a set of predictor variables.Results: Anaemia was prevalent in 84.0% (545) of the children with a majority having microcytic anaemia (59.3%). The prevalence of MdSA was 56.1% (364). Educational level of parents/caregiver (P <  0.001) and site (P = 0.043) had a significant negative effect on the occurrence of MdSA. Stunting, underweight and wasting occurred in 31.3, 13.1 and 6.3% of the children, respectively. Overall, SS was prevalent in 17.1% (111) of the children. The age groups (0.1-1.0 year, P = 0.042 and 1.1-2.0 years, P = 0.008), educational levels (no formal education, P <  0.001 and primary education P = 0.028) and SS (P = 0.035) were significant determinants of MdSA while MdSA (P = 0.035) was the only significant determinant of SS. On the contrary, age group 0.1-1 year (OR = 0.56, P = 0.043) and site (Dibanda, OR = 0.29, P = 0.001) demonstrated a significant protective effect against SS.Conclusions: Moderate to severe anaemia, severe stunting and wasting especially in children not breastfed at all are public health challenges in the conflict-hit area. There is a need for targeted intervention to control anaemia as well as increased awareness of exclusive breast feeding in conflict-hit areas to limit the burden of wasting and stunting. [ABSTRACT FROM AUTHOR]