A “Familiar Foe Revisited": Examining the Relationship between endemic Burkitt’s Lymphoma and Changing Malaria Admissions in The Coastal Region of Kenya

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Mwaniki, Shebe Mohammed, Nyambura Kariuki, Dalton C. Wamalwa, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7539041/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Dec, 2025 Read the published version in BMC Cancer → Version 1 posted 12 You are reading this latest preprint version Abstract Background Burkitt’s lymphoma (BL) is a type of non-Hodgkin lymphoma that may account for more than 40% of childhood malignancies in tropical Africa. The endemic version is common in equatorial Africa, where a BL belt has been mapped. The role of P. falciparum malaria infection in BL has been postulated but not substantiated. The decrease in P. falciparum malaria infection offers an opportunity to examine this association. Methods In this study, we utilized data collected over three decades (1990–2020) and examined the trends in annual admission incidence rates of Burkitt’s lymphoma among pediatric admissions (0–14 years) in relation to the reduction in malaria admissions. Findings: Ninety-five patients with Burkitt’s lymphoma were identified, of whom 72 (75.8%) were male. During the first epoch (1990–1999) and second decade, 29 cases and 62 cases were diagnosed, resulting in 10-year cumulative incidence rates of 93.1 cases and 130.3 cases per 100,000, respectively. In the third decade, 2010–2019, there were only 4 cases (cumulative incidence of 10.2 cases per 100,000). With one-way ANOVA, the F statistic for within- and between-group comparisons was significant (p < 0.0001), indicating that the decline across the three epochs was statistically significant. Similarly, the median parasite density decreased from 13,966.5 (interquartile range (IQR) 123,910) in the first epoch to 7,224 (IQR 107,634) in the third epoch (Kruskal‒Wallis chi-square test, 12.3; P = 0.0021). One-way ANOVA for within- and between-group comparisons was equally significant (p < 0.001). The correlation coefficient between endemic BL and P. falciparum malaria infection was 0.53, indicating a strong positive correlation (P = 0.0024), implying that as P. falciparum malaria infection decreased, the endemic BL incidence rate decreased. Interpretation: There has been a significant reduction in the annual incidence rates of Burkitt’s lymphoma in the coastal region of Kenya. It is plausible that this decrease can be explained by an equally sustained and significant decline in the number of falciparum malaria infections. Figures Figure 1 Figure 2 Figure 3 Figure 22 Introduction Cancer directly causes nearly 10 million deaths annually 1 , with estimates suggesting that 85% of global childhood cancers occur in low- and middle-income countries (LMICs) 2 . Each year, nearly half a million children and adolescents are diagnosed with cancer 3 . In high-income countries, over 80% of childhood cancers are cured or go into remission 4 . However, in LMICs, mortality is extremely high, with a cure rate of less than 50% 4 . This high mortality is driven by a myriad of factors, including a lack of diagnostic infrastructure (under diagnosis and/or misdiagnosis), a lack of timely access to care with advanced presentations, treatment abandonment, death from toxicity and a continuous cycle of relapses due to a lack of optimized treatment 5 , 2 . Furthermore, health information systems are still in their formative stages in LMICs; hence, available statistics on cancer burden are likely to be grossly underestimates. Leukemia is a common childhood cancer worldwide 4 ; however, in tropical Africa, non-Hodgkin lymphoma predominates, accounting for up to 40% of reported childhood malignancies 6 . More than 30 variants of non-Hodgkin’s lymphoma have been described 7 . Burkitt’s lymphoma (BL) is the most common lymphoma in children living in tropical Africa, especially East Africa 8 . BL is a B-cell non-Hodgkin lymphoma characterized by the translocation and deregulation of the MYC gene on the 8th chromosome 8 . Three varieties of this aggressive B-cell lymphoma have been described: endemic, sporadic, and associated with immune deficiency 8 . Overall, BL is endemic to areas where P. falciparum malaria is holo-endemic, especially tropical regions, and hence, the term endemic BL. Although histological examination reveals virtually no difference from other forms of BL, the endemic form frequently presents with tumors of the jaw in children, but other sites, including those with abdominal involvement, are present 9 . There are three postulated predisposing factors for endemic BL: infection with Epstein‒Barr virus (EBV), Plasmodium falciparum infection , and translocation, which usually involves chromosomes 8 and 14 10,11 . The incidence rates of endemic BL are many-fold higher in equatorial Africa, where two of the known predisposing factors (falciparum malaria and EBV infections) are common 8 . Given that EBV is ubiquitously distributed globally even in regions with very low incidence rates of BL, the control of falciparum malaria infection may prevent endemic Burkitt lymphoma 12 . This hypothesis has not been fully examined. The coastal region of Kenya provides an ideal setting for studying the epidemiology of endemic BL, as it lies within the BL belt just south of the equator 9 , 13 . Importantly, while falciparum malaria accounted for more than 40% of inpatient pediatric admissions for decades, a considerable decline was recorded from 2008 14,15 . Given the aforementioned studies reporting a decline in the incidence of P. falciparum malaria, we investigated the change in the epidemiology of endemic BL as well as whether there have been significant changes associated with the changing documented temporal trends for P. falciparum malaria. Methodology Kilifi County Referral Hospital is set at sea level in a P. falciparum malaria endemic area and has a catchment population of approximately half a million people. The hospital equally lies within the endemic Burkitt’s lymphoma belt in Kenya. It has a general pediatric inpatient ward with 60 beds, a high dependency unit with six (6) beds and seven (7) cots and a newborn unit with 42 cots. Kilifi County Referral Hospital further hosts the Kenya Medical Research Institute (KEMRI) Centre for Geographic Medicine Research Coast and the KEMRI-Wellcome Trust Research Program. Since 1999, through the research program, continuous surveillance has been initiated at the hospital with the aims of (i) providing a sampling frame for long-term epidemiological and related studies; (ii) evaluating the impact of new community-based interventions against infectious diseases; and (iii) establishing a base for clinical trials and other advanced interventional studies. On admission, discharge or death, standardized clinical and laboratory data are collected for each child 14 . These include a complete history and physical examination, a routine complete blood count, a malaria slide for examination, and blood culture for surveillance of invasive bacterial infections. Other tests (lumbar puncture for cerebrospinal fluid analysis; urea, creatinine and electrolytes; urinalysis; and urine culture, imaging or radiological examination) are guided by clinical indications. Overall, the management of children admitted follows the Kenya National and World Health Organization’s recommendations 16 . Aside from the above routine investigation, for children with a preliminary clinical impression of “possible malignancy”, tissue specimens (excision biopsy, fine needle aspiration, bone marrow aspiration and cerebral spinal fluid analysis) are obtained for pathological examination and definitive diagnosis. Study population This study utilized data from all children aged 0–14 years admitted to the study site from 1990–2020. From this dataset, total admissions aged 0–14 years and admissions with a final discharge diagnosis of Burkitt’s lymphoma (confirmed by tissue specimen examination) were identified. Likewise, children with a final diagnosis of P. falciparum malaria (confirmed by blood slide microscopic examination) were obtained. To control for changes in the population in the catchment area, the at-risk population (0–14 years old) was estimated from census data for Kilifi County and used as the denominator. To estimate this number, census estimates from 1989, 1999, 2009 and 2019 were utilized. This resulted in estimated populations at risk of 165,674, 231,157 and 310,615 for the 1st (1990–1999), 2nd (2000–2009) and 3rd (2010–2020) epochs, respectively. The annual growth rate of the population under 14 years steadily increased over the three decades at the following annual rates: from 1989–1999 (6,548.3 per year), 1999–2009 (7,945.8 per year), and from 2009–2019, it further increased to 9,630.0 per year. This growth rate was input into a piecewise linear interpolation calculation to smooth the population numbers. This approach assumed a linear growth rate with uniformity for each age group within the 0–14-year range. Sample size To examine the minimum number of BL cases needed to answer the main objective (sample size), we applied the approach for a longitudinal study estimating the main effect of a time-varying exposure as described by Basagaña and Spiegelman 17 . In this case, an a priori assumption that P. falciparum malaria infection influences endemic Burkitt lymphoma was made; hence, malaria infection was taken as the time-varying exposure. Data for P. falciparum malaria point prevalence were obtained from a 25-year-long study performed from 1990–2014 among children admitted to Kilifi County referral hospital 18 . The malaria-positive fraction(s) applied in the computation are shown below. Year 1990 1996 2002 2008 2014 2020 Malaria positive fraction 0.4 0.48 0.50 0.12 0.22 0.22 Using the above information, we found that with a minimum of 37 cases, the study detected at least a 20% change in the annual incidence rates of endemic BL. Study procedures Secondary anonymized data from participants meeting the inclusion criteria were utilized. In virtually all the instances, these data were retrieved from secure password protected electronic databases by the data manager at the KEMRI Center for Geographic Medicine Research Coast (CGMRC) (KEMRI-CGMRC). Permission for the same was granted by the KEMRI-CGMRC data governance committee. The data were initially exported into Excel. These included final discharge diagnosis, available laboratory investigations, clinical history, pathology findings from biopsies, imaging, and treatment regimens used. Finally, the data were imported into STATA for manipulation and analysis. Data management and analysis To ensure that no cases were missed, all available medical records for cases captured as pediatric cancers at admission discharge were initially reviewed by Michael Mwaniki and Shebe Mohammed. A second review was then conducted for those diagnosed with Burkitt’s lymphoma. For trend comparisons, data for all total pediatric admissions aged 0–14 years and total pediatric admissions with a final diagnosis at discharge of P. falciparum malaria were similarly prepared for manipulation and analysis. We conducted the final analysis via STATA (Stata Corp, College Station, TX, USA). Detailed analysis of the data set focused on demographic data, tumor site and presentation, and trend analysis of annual incidence rates controlled for the at-risk catchment population. Specifically, to test for the statistical significance of the incidence rates of Burkitt’s lymphoma across the three epochs, one-way ANOVA was performed. Similarly, one-way ANOVA was used to calculate the difference in malaria incidence across the three epochs, with the percentage positivity and malaria parasite density used as proxies. Finally, correction for the correlation between malaria and endemic Burkitt’s lymphoma was explored via linear regression, and the correlation coefficient was calculated. Results The total number of admissions for the entire period from 1990–2020 was 124,298, of which 69,468 (56%) were males. Between 1990 and 1999, admissions increased by 236.7 per year ( p = < 0.0001 ). In the second ten-year period, the number of admissions decreased by 129.2 for each unit change in year ( p = 0.0029 ). The number of annual admissions then remained relatively unchanged during the last decade, showing only a marginal reduction of 8.6 admissions per year, a trend that was not statistically significant ( p = 0.9105 ). From the admission records, 95 patients with Burkitt’s lymphoma were identified, of whom 72 (75.8%) were male. The median age at diagnosis was 6.0 years, with an interquartile range (IQR) of 2.72–8.28 for boys and 7.0 (3.25–10.75) for girls, but the difference in age at presentation was not statistically significant (Mann‒Whitney U test 513.0, p value of 0.252). Most of the subjects presented with at least one primary mass in the jaw (67.7%). Many patients had secondary associated sites, especially the abdomen (40%), central nervous system (27%) and bone marrow (20%). Anemia (hemoglobin (Hb) < 10 g/dl) was found in 38 (48.7%) of the patients, whereas 10 (12.8%) of the patients had severe anemia, defined as Hb < 7 g/dl at admission. None of the patients had thrombocytopenia, defined as a platelet count less than 150,000 per microlitre. Furthermore, three subjects (4.6%) had jaundice, with four having clinically appreciable hepatomegaly and an additional 12 (12.6%) having splenomegaly. Twenty subjects had fever (> 37.5°C). None of the patients were hypoxemic (pulse oximetry < 90%) on admission. The annual hospital admission rates were calculated for endemic Burkitt’s lymphoma patients first, with the total number of pediatric admissions aged 0–14 years as the comparator. Furthermore, the same was recalculated via census estimates for the overall population at risk (0–14 years) in Kilifi County over the study period to determine the population incidence rate. The annual hospital admission incidence rates of Burkitt’s lymphoma increased continuously, with the highest admission incidence rate being 196.1 (95% CI 74.56–317.64) per 100,000 admissions in 2001. This corresponded to an incidence rate of 4.0 (95% CI 0.08–7.92) per 100,000 when the overall at-risk population in the catchment area was controlled (Table 1 ). The comparison between the 10-year periods revealed a decrease in new cases in the third epoch. The first period (1990–1999) had 37,589 admissions and 29 cases of Burkitt's lymphoma, which translated to a 10-year cumulative incidence rate of 93.1 cases per 100,000. The second period had the highest number of cases of Burkitt’s disease (62 cases), translating to a 10-year cumulative incidence rate of 130.3 cases per 100,000. The final period had the lowest number of cases, at just 4, with a cumulative incidence of 10.2 cases per 100,000.) When one-way ANOVA was used to test for statistical significance of the incidence rate of endemic Burkitt’s lymphoma across the three epochs, the F statistic within and between groups was significant (p < 0.0001) (Fig. 1 ), indicating that the overall decline was statistically significant. Table 1 Incidence rates of Burkitt’s lymphoma per 100,000 admissions and per 100,000 under 14 population estimates Year Number of Burkitt’s Lymphoma cases admitted Total Admissions Incidence rate per 100,000 admissions 95% CI Incidence rate per 100,000 of the catchment population 95% CI 1990 0 2395 0.0 (0, 0) 0.0 0.00–0.00 1991 0 3549 0.0 (0, 0) 0.0 0.00–0.00 1992 0 2949 0.0 (0, 0) 0.0 0.00–0.00 1993 3 3127 95.9 (0, 204.44) 1.6 0.00-4.08 1994 7 4124 169.7 (43.97, 295.43) 3.5 0.00-7.17 1995 3 3747 80.1 (0, 170.72) 1.5 0.00-3.90 1996 3 4114 72.9 (0, 155.41) 1.4 0.00-3.72 1997 3 4305 69.7 (-0, 148.57) 1.4 0.00-3.72 1998 8 4182 191.3 (58.74, 323.86) 3.6 0.00-7.32 1999 2 5134 39.0 (0, 93.02) 0.9 0.00-2.76 2000 6 5126 117.1 (23.42, 210.78) 2.5 0.00-5.60 2001 10 5100 196.1 (74.56, 317.64) 4.0 0.08–7.92 2002 7 4797 145.9 (37.81, 253.99) 2.7 0.00-5.92 2003 6 5459 109.9 (21.96, 197.84) 2.3 0.00-5.27 2004 4 4963 80.6 (1.61, 159.59) 1.5 0.00-3.90 2005 8 4612 173.5 (53.28, 293.72) 2.9 0.00-6.24 2006 7 4819 145.3 (37.68, 252.92) 2.4 0.00-5.44 2007 10 4260 234.7 (89.22, 380.18) 3.4 0.00-7.01 2008 2 4010 49.9 (0, 119.04) 0.7 0.00-2.34 2009 2 4429 45.2 (0, 107.81) 0.6 0.00-2.12 2010 0 4035 0.0 (0, 0) 0.0 0.00–0.00 2011 0 3982 0.0 (0, 0) 0.0 0.00–0.00 2012 0 3367 0.0 (0, 0) 0.0 0.00–0.00 2013 0 2687 0.0 (0, 0) 0.0 0.00–0.00 2014 1 3932 25.4 (0, 75.22) 0.3 0.00-1.37 2015 1 4090 24.4 (0, 72.27) 0.3 0.00-1.37 2016 1 3660 27.3 (0, 80.83) 0.3 0.00-1.37 2017 0 2187 0.0 (0, 0) 0.0 0.00–0.00 2018 0 3752 0.0 (0, 0) 0.0 0.00–0.00 2019 0 4056 0.0 (0, 0) 0.0 0.00–0.00 2020 1 3327 30.1 (0, 89.05) 0.2 0.00-1.08 In 1990, 847 cases were positive for P. falciparum malaria, out of 2,395 total admissions, resulting in a Falciparum malaria positivity percentage of 35% of all admissions. Overall, in the first epoch (1990–2000), the number of positive cases and the Falciparum malaria positivity fraction continued to increase, reaching their highest point in 1992, with 1,595 positive cases and a positivity percentage of 54%. The median parasite density in this first epoch was 13,966.5 (IQR 123,910). In the second and third stages, the number of positive cases, total admissions, and positivity percentage decreased, with the lowest values occurring in 2017. The median parasite density also rapidly decreased over the two epochs, being 9,744 (IQR 112440) and 7,224 (IQR 107,634) in the second and third epochs, respectively. The decline across the three epochs was significant (Kruskal‒Wallis chi-square test, 12.3; P = 0.0021). This difference was similarly significant when one-way ANOVA was applied (p < 0.001) (Fig. 2 ). Finally, to analyze the relationship between endemic Burkitt’s lymphoma cases and Falciparum malaria infection point prevalence, linear regression was applied, as displayed in Fig. 3 . The correlation coefficient was 0.53, indicating a moderately strong positive correlation (P = 0.0024). Discussion More than 100,000 children are diagnosed with cancer in the sub-Saharan Africa region 19 These estimates are imprecise and grossly underestimate the burden largely because of the underdeveloped healthcare infrastructure across all aspects of cancer management (absent cancer registries, paucity of healthcare professionals trained in cancer diagnosis and management, poor access to treatment, and limited cancer research) in the region 19 . Overall, mortality is equally high, with a cure rate lower than 50% in many countries 6 . Non-Hodgkin lymphoma (NHL) is one of the most prevalent childhood cancers in sub-Saharan Africa 20 . The bulk (more than 50%) of NHLs are composed of BL, and the proportion of BL may exceed 60–80% within the endemic BL belt 21 . The endemic BL region generally overlies the Plasmodium malaria-endemic countries in tropical Africa 21 . Given the consistently documented overlay of the two conditions, repeated P. falciparum malaria infection has been postulated to play a central role in the pathogenesis of endemic BL, resulting in higher incidence rates 22 . However, this postulated association has never been fully examined. Therefore, this study is one of the largest and longest observational studies tracking both the incidence rates of endemic BL and P. falciparum malaria infections within the BL region. Analysis of the cumulative BL cases over the study period revealed that the median age at presentation was approximately 6.0 years, with an IQR of approximately 3–8 years for boys and 7.0 (3–11) years for girls, which is similar to that reported in other studies 12 . The annual incidence rates were highest in the mid-1990s, at approximately 4.8 per 100,000 of the population at risk, which was within the 3–6 per 100,000 uniformly documented within the endemic Burkitt’s lymphoma belt 21 . From the mid-2000s, a gradual decline was recorded, reaching a nadir of 0.2 cases per 100,000 people by the year 2020. Malaria infections were very common in the first 15 years (1990-2000s), with close to 50% of all admitted children being diagnosed with falciparum malaria clinically as well as through a positive malaria blood smear. From the mid-2000s, the number of malaria-positive cases decreased to less than 20% of all pediatric admissions. This decline was sustained for the remainder of the study period. The year-over-year decline in the percentage of children admitted with malaria was significant ( P value = < 0.0001). This significant decline in malaria infections has been documented in other hospitals and community-based studies 15 , 18 . This phenomenon may be driven by a combination of preventive strategies, such as early effective treatment, indoor residue spraying, and the use of long-lasting insecticide-treated mosquito nets. Malaria parasite density may correlate with population-level variation in infection burden 23 , with high malaria prevalence areas tending to be associated with higher parasite density among those infected and vice versa 23 . In this study, the malaria parasite density closely followed a similar trajectory to that of the malaria-positive fractions. The year-over-year decrease in malaria parasite density across the study period was significant ( P value = < 0.0001). Therefore, although this was a hospital-based study, a significant decrease in both the percentage of children admitted with positive malaria slides and malaria parasite density plausibly indicates an equally significant decline in overall P. falciparum malaria prevalence within the catchment population. Finally, this study examined the correlation between P. falciparum malaria reduction and incidence rates of endemic BL. The correlation coefficient was 0.53, indicating a moderately strong positive correlation (P = 0.0024). Since P. falciparum malaria is postulated to play a crucial role in the pathogenesis of endemic BL, reducing and/or eradicating malaria infection has been advocated as a plausible preventive strategy for endemic BL 24 . However, few studies have explored this relationship, and the uncertainties of any association still abound. Our study, which spans three decades, is one of the first to clearly demonstrate that a sustained reduction in P. falciparum malaria infection was associated with a significant decline in the incidence rates of endemic BL. Notably, a lag of at least half a decade was discernible between the years of noticeable reduction in the malaria positivity fraction and malaria parasite density before any reduction in annual cases of endemic BL was documented. This may imply that seasonal or short-lived variations in malaria incidence or transmission dynamics have negligible impacts on the incidence rates of endemic BL and that sustained reduction is a requirement. Furthermore, although the onset of partial immunity in older children leading to repeated cycles of infections that are cleared without treatment may play a role in the pathogenesis of the malignancy 10 , 12 , the time it takes for this to “ unlock ” the process leading to B-cell immortalization is unknown. It is therefore possible that the high number of endemic BL cases witnessed during the initial years of malaria infection reduction depicts individuals in whom the pathological process may have started in the earlier years of very high malaria prevalence. Overall, our study demonstrates the transformation of an endemic BL picture into a level of annual incidence rates similar to those experienced within sporadic BL regions. Previous studies that have examined the relationships between BL and malaria have reported mixed findings. A study conducted in Uganda between 1976 and 2005 concluded that the distribution of Burkitt’s lymphoma did not differ across the three decades 25 . However, that study was conducted during decades of sustained high malaria prevalence in the region. Therefore, given the postulated role of P. falciparum malaria in this pathogenesis, it is unlikely that a discernible change would have been demonstrated. Another recently published article equally explored global trends in pediatric lymphomas 26 . That study noted an increase in BL across 8 of the 15 global regions. However, the study used data collected from 1988–2012, a period of high sustained malaria transmission 26 . In summary, the findings of our study are close to what was reported in a publication from Tanzania that utilized data collected between 2000 and 2009 27 . That study revealed that the number of BL cases was greater in the first period (2000–2004) than in the second period (2005–2009), although there was uncertainty in the significance of the observed decline 27 . Notably, the Tanzania study utilized data across a much shorter observation period (one decade). Furthermore, this was conducted during a period of transition from the high malaria incidence and the initial years of declining malaria transmission, which may explain the observed uncertainty. Significance of the study findings Pediatric cancers are expensive to diagnose and treat, with the estimated cost per diagnosis of a new single case being more than $ 31,000 28 . With respect to endemic BL, treatment outcomes in sub-Saharan Africa remain suboptimal 29 , and the cost for treating a single patient is estimated at close to $ 12,829 30 . Although this puts the treatment costs within the boundaries of what would be considered cost effective by various models, including the WHO CHOICE model 30 , it is still prohibitive as a direct cost within the fragile healthcare systems in most SSA countries. On the other hand, malaria control programs are among the most cost effective and can be deployed rapidly at scale 31 . The median financial cost of protecting one person for one year may be well under $ 5 for most of the proven interventions, such as insecticide-treated nets, indoor residue spraying, and intermittent preventive therapy, with a considerable benefit-to-cost ratio 31 . Therefore, our study demonstrates that malaria infection control programs may lead to a significant reduction in the burden of endemic BL, and a malignancy that is responsible for 40–60% of the pediatric cancers within large territories within the endemic BL zone is thus crucial. This finding lends credence to the postulation of the association between BL and P. falciparum malaria as well as suggestions that sustained malaria prevention could be a viable control strategy for this malignancy. Limitations First, the diagnostic capabilities for cancers in Kenya and other SSA regions 32 are suboptimal, which may result in under diagnosis. Second, there is a paucity of knowledge on community health-seeking behavior for childhood cancers. Myths and misconceptions on the prospects of treatment and outcomes may lead to many children not being brought to formal healthcare systems 33 . Third, this study was conducted at a single site in one country. The pattern of referral may have changed, although there was no increase in the number of BL cases in adjacent hospitals during this period. Fourth, although the results may be generalizable to other similar regions, multisite and multi-country studies are needed to address this important question equally. Conclusion There has been a significant decrease in the annual incidence rate of endemic BL associated with a sustained reduction in malaria incidence. Importantly, this is the first study to effectively demonstrate such phenomena and hence lends credence to the postulated association between endemic BL and P. falciparum malaria. However, multisite, multi-country studies exploring this topic within the endemic BL belt are needed. Abbreviations ANOVA Analysis of Variance BL Burkitt’s lymphoma CGMRC Centre for Geographic Medicine Research Coast EBV Epstein‒Barr virus ERC Ethical Review Committee HB Haemoglobin IQR Interquartile Range KEMRI Kenya Medical Research Institute KNH Kenyatta National Hospital LMICS Low- and Middle-Income Countries MYC Myelo-Cytomatosis gene NHL Non-Hodgkin lymphoma UON University of Nairobi USA United States of America WHO World Health Organization’s Declarations Ethical considerations . Prospective surveillance (both inpatient and outpatient) focused on describing common childhood illness was instituted at the Kilifi site by Kenya Medical Research Institute (KEMRI) Center for Geographic Medicine Research Coast (CGMRC) from 1989. All Guardians are requested for consent to use the data of admitted children prospectively at the point of admission. This study utilized secondary anonymized data from the site and further individual consent to analyze the data was deemed not necessary. Importantly, studies conducted via KEMRI adhere to internationally accepted norms including the Declaration of Helsinki. Further, this study was approved by Kenyatta National Hospital-University of Nairobi Ethical Review Committee (KNH-UON ERC), approval number P298/04/2022 . Consent for publication All the authors reviewed and approved the final manuscript for publication. No other consent for publication was required. Data Availability Datasets generated and analyzed during this study are available upon direct request to the corresponding author via the Kenya Medical Research Institute. Competing interests The authors declare that they have no competing interests. The views expressed do not necessarily represent the views of the authors’ affiliated institutions. Funding This study was supported by the Welcome Trust, grant code (077092/B/05/Z) and Kenya Medical Research Institute. The funder had no role in the study design, data collection, and analysis or manuscript preparation. Authors’ contributions MKM was the lead author; he oversaw the data collection and analysis and drafted the initial manuscript. SM assisted in data collection and was involved in the review of the final manuscript. FM assisted in the data analysis, drafted the initial manuscript and reviewed the final manuscript. CRN, DCW & NK were involved at various points in the drafting of the manuscript and extensive review of the final submitted manuscript. All the authors reviewed and approved the final manuscript for submission. Acknowledgements Not applicable References Sung H et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin 71, (2021). Joko-Fru WY et al. 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Cancer Epidemiol. 2021;73:101965. Aka P et al. Incidence and trends in Burkitt lymphoma in northern Tanzania from 2000 to 2009. Pediatr Blood Cancer 59, (2012). Githang’a J, et al. The cost-effectiveness of treating childhood cancer in 4 centers across sub-Saharan Africa. Cancer. 2021;127:787–93. Ozuah NW, Lubega J, Allen CE, El-Mallawany NK. Five decades of low intensity and low survival: Adapting intensified regimens to cure pediatric Burkitt lymphoma in Africa. Blood Advances vol. 4 at https://doi.org/10.1182/bloodadvances.2020002178 (2020). Denburg AE, et al. The cost effectiveness of treating Burkitt lymphoma in Uganda. Cancer. 2019;125:1918–28. Conteh L, et al. Costs and Cost-Effectiveness of Malaria Control Interventions: A Systematic Literature Review. Value Health. 2021;24:1213–22. Boyle P, Ngoma T, Sullivan R, Brawley O. Cancer in Africa: The way forward. Ecancermedicalscience 13, (2019). Renner LA, McGill D. Exploring factors influencing health-seeking decisions and retention in childhood cancer treatment programmes: perspectives of parents in Ghana. Ghana Med J 50, (2016). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 18 Dec, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 12 Nov, 2025 Reviews received at journal 11 Nov, 2025 Reviewers agreed at journal 06 Nov, 2025 Reviewers agreed at journal 04 Nov, 2025 Reviews received at journal 26 Oct, 2025 Reviewers agreed at journal 21 Oct, 2025 Reviewers agreed at journal 20 Oct, 2025 Reviewers invited by journal 18 Sep, 2025 Editor assigned by journal 18 Sep, 2025 Editor invited by journal 15 Sep, 2025 Submission checks completed at journal 13 Sep, 2025 First submitted to journal 13 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7539041","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":521715098,"identity":"2eb352c9-1dcc-4d86-8c26-0cf8190fb5eb","order_by":0,"name":"Michael K. 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Newton","email":"","orcid":"","institution":"Kenya Medical Research Institute","correspondingAuthor":false,"prefix":"","firstName":"Charles","middleName":"R.","lastName":"Newton","suffix":""}],"badges":[],"createdAt":"2025-09-04 20:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7539041/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7539041/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-025-15450-9","type":"published","date":"2025-12-18T15:58:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":92425600,"identity":"776844fe-dbf3-417f-ab3b-22e2219fe6c4","added_by":"auto","created_at":"2025-09-29 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15:09:02","extension":"html","order_by":24,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":133937,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7539041/v1/4d1ff9b4e48a9cbff1fb130d.html"},{"id":92425663,"identity":"ae9db3db-595b-4705-acff-27d06912c945","added_by":"auto","created_at":"2025-09-29 15:09:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":242082,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eIncidence rate of endemic Burkitt’s lymphoma per 100,000 across the three epochs\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7539041/v1/db01d9b727d208b0203dd920.jpeg"},{"id":92426075,"identity":"dd00e167-0b2a-4490-a0c9-092c08eec971","added_by":"auto","created_at":"2025-09-29 15:17:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":247412,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eTrends of Malaria parasitedensity and Malaria positivity fraction and prevalence of Malaria across the three epochs\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7539041/v1/1d69b6670a6206ab262a5606.png"},{"id":92425670,"identity":"c5a4199a-3627-4083-be06-a422966960ac","added_by":"auto","created_at":"2025-09-29 15:09:04","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":20976,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eIncidence rate of endemic Burkitts Lyphoma controlled for changing malaria period prevalence and for the at-risk population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ei) \u003cem\u003eEach ten year epoch is represented with distinct identifying colour as shown in the key\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eii) \u003cem\u003eThe annual incidence rate of endemic Burkitt’s Lymphoma for every single year is marked accordingly across the three epochs\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eiii) The correlation coefficient between these two variables was approximately 0.53. This value indicates a strong positive correlation (P=0.0024), suggesting that as the malaria prevalence decreases, endemic Burkitt’s lymphoma incidence rate equally decreases.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7539041/v1/74a73ebba535d22b04929d8c.png"},{"id":92425652,"identity":"b92ee154-c771-4c8e-a236-a717eb794fbc","added_by":"auto","created_at":"2025-09-29 15:09:02","extension":"png","order_by":22,"title":"Figure 22","display":"","copyAsset":false,"role":"figure","size":20976,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eIncidence rate of endemic Burkitts Lyphoma controlled for changing malaria period prevalence and for the at-risk population\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ei) \u003cem\u003eEach ten year epoch is represented with distinct identifying colour as shown in the key\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eii) \u003cem\u003eThe annual incidence rate of endemic Burkitt’s Lymphoma for every single year is marked accordingly across the three epochs\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eiii) The correlation coefficient between these two variables was approximately 0.53. This value indicates a strong positive correlation (P=0.0024), suggesting that as the malaria prevalence decreases, endemic Burkitt’s lymphoma incidence rate equally decreases.\u003c/p\u003e","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7539041/v1/02d311f59c9259e9178ec196.png"},{"id":98815035,"identity":"d7029b0f-e0b7-435c-b432-efa9febdc232","added_by":"auto","created_at":"2025-12-22 16:13:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1395035,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7539041/v1/2eaa17dc-a7be-4696-aa9c-01dc021afbda.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A “Familiar Foe Revisited\": Examining the Relationship between endemic Burkitt’s Lymphoma and Changing Malaria Admissions in The Coastal Region of Kenya","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCancer directly causes nearly 10\u0026nbsp;million deaths annually\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e, with estimates suggesting that 85% of global childhood cancers occur in low- and middle-income countries (LMICs)\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Each year, nearly half a million children and adolescents are diagnosed with cancer\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In high-income countries, over 80% of childhood cancers are cured or go into remission\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. However, in LMICs, mortality is extremely high, with a cure rate of less than 50%\u003csup\u003e4\u003c/sup\u003e. This high mortality is driven by a myriad of factors, including a lack of diagnostic infrastructure (under diagnosis and/or misdiagnosis), a lack of timely access to care with advanced presentations, treatment abandonment, death from toxicity and a continuous cycle of relapses due to a lack of optimized treatment\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Furthermore, health information systems are still in their formative stages in LMICs; hence, available statistics on cancer burden are likely to be grossly underestimates.\u003c/p\u003e\u003cp\u003eLeukemia is a common childhood cancer worldwide\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e; however, in tropical Africa, non-Hodgkin lymphoma predominates, accounting for up to 40% of reported childhood malignancies\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. More than 30 variants of non-Hodgkin\u0026rsquo;s lymphoma have been described\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Burkitt\u0026rsquo;s lymphoma (BL) is the most common lymphoma in children living in tropical Africa, especially East Africa\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. BL is a B-cell non-Hodgkin lymphoma characterized by the translocation and deregulation of the \u003cem\u003eMYC\u003c/em\u003e gene on the 8th chromosome\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Three varieties of this aggressive B-cell lymphoma have been described: endemic, sporadic, and associated with immune deficiency\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Overall, BL is endemic to areas where P. falciparum malaria is holo-endemic, especially tropical regions, and hence, the term endemic BL. Although histological examination reveals virtually no difference from other forms of BL, the endemic form frequently presents with tumors of the jaw in children, but other sites, including those with abdominal involvement, are present\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThere are three postulated predisposing factors for endemic BL: infection with Epstein‒Barr virus (EBV), \u003cem\u003ePlasmodium falciparum infection\u003c/em\u003e, and translocation, which usually involves chromosomes 8 and 14\u003csup\u003e10,11\u003c/sup\u003e. The incidence rates of endemic BL are many-fold higher in equatorial Africa, where two of the known predisposing factors (falciparum malaria and EBV infections) are common\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Given that EBV is ubiquitously distributed globally even in regions with very low incidence rates of BL, the control of falciparum malaria infection may prevent endemic Burkitt lymphoma \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. This hypothesis has not been fully examined.\u003c/p\u003e\u003cp\u003eThe coastal region of Kenya provides an ideal setting for studying the epidemiology of endemic BL, as it lies within the BL belt just south of the equator\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Importantly, while falciparum malaria accounted for more than 40% of inpatient pediatric admissions for decades, a considerable decline was recorded from 2008\u003csup\u003e14,15\u003c/sup\u003e. Given the aforementioned studies reporting a decline in the incidence of P. falciparum malaria, we investigated the change in the epidemiology of endemic BL as well as whether there have been significant changes associated with the changing documented temporal trends for P. falciparum malaria.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eKilifi County Referral Hospital is set at sea level in a P. falciparum malaria endemic area and has a catchment population of approximately half a million people. The hospital equally lies within the endemic Burkitt\u0026rsquo;s lymphoma belt in Kenya. It has a general pediatric inpatient ward with 60 beds, a high dependency unit with six (6) beds and seven (7) cots and a newborn unit with 42 cots. Kilifi County Referral Hospital further hosts the Kenya Medical Research Institute (KEMRI) Centre for Geographic Medicine Research Coast and the KEMRI-Wellcome Trust Research Program. Since 1999, through the research program, continuous surveillance has been initiated at the hospital with the aims of (i) providing a sampling frame for long-term epidemiological and related studies; (ii) evaluating the impact of new community-based interventions against infectious diseases; and (iii) establishing a base for clinical trials and other advanced interventional studies. On admission, discharge or death, standardized clinical and laboratory data are collected for each child\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. These include a complete history and physical examination, a routine complete blood count, a malaria slide for examination, and blood culture for surveillance of invasive bacterial infections. Other tests (lumbar puncture for cerebrospinal fluid analysis; urea, creatinine and electrolytes; urinalysis; and urine culture, imaging or radiological examination) are guided by clinical indications. Overall, the management of children admitted follows the Kenya National and World Health Organization\u0026rsquo;s recommendations \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAside from the above routine investigation, for children with a preliminary clinical impression of \u0026ldquo;possible malignancy\u0026rdquo;, tissue specimens (excision biopsy, fine needle aspiration, bone marrow aspiration and cerebral spinal fluid analysis) are obtained for pathological examination and definitive diagnosis.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy population\u003c/h2\u003e\u003cp\u003eThis study utilized data from all children aged 0\u0026ndash;14 years admitted to the study site from 1990\u0026ndash;2020. From this dataset, total admissions aged 0\u0026ndash;14 years and admissions with a final discharge diagnosis of Burkitt\u0026rsquo;s lymphoma (confirmed by tissue specimen examination) were identified. Likewise, children with a final diagnosis of P. falciparum malaria (confirmed by blood slide microscopic examination) were obtained. To control for changes in the population in the catchment area, the at-risk population (0\u0026ndash;14 years old) was estimated from census data for Kilifi County and used as the denominator. To estimate this number, census estimates from 1989, 1999, 2009 and 2019 were utilized. This resulted in estimated populations at risk of 165,674, 231,157 and 310,615 for the 1st (1990\u0026ndash;1999), 2nd (2000\u0026ndash;2009) and 3rd (2010\u0026ndash;2020) epochs, respectively. The annual growth rate of the population under 14 years steadily increased over the three decades at the following annual rates: from 1989\u0026ndash;1999 (6,548.3 per year), 1999\u0026ndash;2009 (7,945.8 per year), and from 2009\u0026ndash;2019, it further increased to 9,630.0 per year. This growth rate was input into a piecewise linear interpolation calculation to smooth the population numbers. This approach assumed a linear growth rate with uniformity for each age group within the 0\u0026ndash;14-year range.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSample size\u003c/h3\u003e\n\u003cp\u003eTo examine the minimum number of BL cases needed to answer the main objective (sample size), we applied the approach for a longitudinal study estimating the main effect of a time-varying exposure as described by \u003cem\u003eBasaga\u0026ntilde;a and Spiegelman\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. In this case, an \u003cem\u003ea priori\u003c/em\u003e assumption that P. falciparum malaria infection influences endemic Burkitt lymphoma was made; hence, malaria infection was taken as the time-varying exposure. Data for P. falciparum malaria point prevalence were obtained from a 25-year-long study performed from 1990\u0026ndash;2014 among children admitted to Kilifi County referral hospital\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The malaria-positive fraction(s) applied in the computation are shown below.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1990\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1996\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2002\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2008\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMalaria positive fraction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eUsing the above information, we found that with a minimum of 37 cases, the study detected at least a 20% change in the annual incidence rates of endemic BL.\u003c/p\u003e\n\u003ch3\u003eStudy procedures\u003c/h3\u003e\n\u003cp\u003eSecondary anonymized data from participants meeting the inclusion criteria were utilized. In virtually all the instances, these data were retrieved from secure password protected electronic databases by the data manager at the KEMRI Center for Geographic Medicine Research Coast (CGMRC) (KEMRI-CGMRC). Permission for the same was granted by the KEMRI-CGMRC data governance committee.\u003c/p\u003e\u003cp\u003eThe data were initially exported into Excel. These included final discharge diagnosis, available laboratory investigations, clinical history, pathology findings from biopsies, imaging, and treatment regimens used. Finally, the data were imported into STATA for manipulation and analysis.\u003c/p\u003e\n\u003ch3\u003eData management and analysis\u003c/h3\u003e\n\u003cp\u003eTo ensure that no cases were missed, all available medical records for cases captured as pediatric cancers at admission discharge were initially reviewed by Michael Mwaniki and Shebe Mohammed. A second review was then conducted for those diagnosed with Burkitt\u0026rsquo;s lymphoma. For trend comparisons, data for all total pediatric admissions aged 0\u0026ndash;14 years and total pediatric admissions with a final diagnosis at discharge of P. falciparum malaria were similarly prepared for manipulation and analysis. We conducted the final analysis via STATA (Stata Corp, College Station, TX, USA). Detailed analysis of the data set focused on demographic data, tumor site and presentation, and trend analysis of annual incidence rates controlled for the at-risk catchment population. Specifically, to test for the statistical significance of the incidence rates of Burkitt\u0026rsquo;s lymphoma across the three epochs, one-way ANOVA was performed. Similarly, one-way ANOVA was used to calculate the difference in malaria incidence across the three epochs, with the percentage positivity and malaria parasite density used as proxies. Finally, correction for the correlation between malaria and endemic Burkitt\u0026rsquo;s lymphoma was explored via linear regression, and the correlation coefficient was calculated.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe total number of admissions for the entire period from 1990\u0026ndash;2020 was 124,298, of which 69,468 (56%) were males. Between 1990 and 1999, admissions increased by 236.7 per year (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/em\u003e). In the second ten-year period, the number of admissions decreased by 129.2 for each unit change in year (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.0029\u003c/em\u003e). The number of annual admissions then remained relatively unchanged during the last decade, showing only a marginal reduction of 8.6 admissions per year, a trend that was not statistically significant (\u003cem\u003ep\u0026thinsp;=\u0026thinsp;0.9105\u003c/em\u003e).\u003c/p\u003e\u003cp\u003eFrom the admission records, 95 patients with Burkitt\u0026rsquo;s lymphoma were identified, of whom 72 (75.8%) were male. The median age at diagnosis was 6.0 years, with an interquartile range (IQR) of 2.72\u0026ndash;8.28 for boys and 7.0 (3.25\u0026ndash;10.75) for girls, but the difference in age at presentation was not statistically significant (Mann‒Whitney U test 513.0, p value of 0.252). Most of the subjects presented with at least one primary mass in the jaw (67.7%). Many patients had secondary associated sites, especially the abdomen (40%), central nervous system (27%) and bone marrow (20%). Anemia (hemoglobin (Hb)\u0026thinsp;\u0026lt;\u0026thinsp;10 g/dl) was found in 38 (48.7%) of the patients, whereas 10 (12.8%) of the patients had severe anemia, defined as Hb\u0026thinsp;\u0026lt;\u0026thinsp;7 g/dl at admission. None of the patients had thrombocytopenia, defined as a platelet count less than 150,000 per microlitre. Furthermore, three subjects (4.6%) had jaundice, with four having clinically appreciable hepatomegaly and an additional 12 (12.6%) having splenomegaly. Twenty subjects had fever (\u0026gt;\u0026thinsp;37.5\u0026deg;C). None of the patients were hypoxemic (pulse oximetry\u0026thinsp;\u0026lt;\u0026thinsp;90%) on admission.\u003c/p\u003e\u003cp\u003eThe annual hospital admission rates were calculated for endemic Burkitt\u0026rsquo;s lymphoma patients first, with the total number of pediatric admissions aged 0\u0026ndash;14 years as the comparator. Furthermore, the same was recalculated via census estimates for the overall population at risk (0\u0026ndash;14 years) in Kilifi County over the study period to determine the population incidence rate.\u003c/p\u003e\u003cp\u003eThe annual hospital admission incidence rates of Burkitt\u0026rsquo;s lymphoma increased continuously, with the highest admission incidence rate being 196.1 (95% CI 74.56\u0026ndash;317.64) per 100,000 admissions in 2001. This corresponded to an incidence rate of 4.0 (95% CI 0.08\u0026ndash;7.92) per 100,000 when the overall at-risk population in the catchment area was controlled (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The comparison between the 10-year periods revealed a decrease in new cases in the third epoch. The first period (1990\u0026ndash;1999) had 37,589 admissions and 29 cases of Burkitt's lymphoma, which translated to a 10-year cumulative incidence rate of 93.1 cases per 100,000. The second period had the highest number of cases of Burkitt\u0026rsquo;s disease (62 cases), translating to a 10-year cumulative incidence rate of 130.3 cases per 100,000. The final period had the lowest number of cases, at just 4, with a cumulative incidence of 10.2 cases per 100,000.) When one-way ANOVA was used to test for statistical significance of the incidence rate of endemic Burkitt\u0026rsquo;s lymphoma across the three epochs, the F statistic within and between groups was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), indicating that the overall decline was statistically significant.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIncidence rates of Burkitt\u0026rsquo;s lymphoma per 100,000 admissions and per 100,000 under 14 population estimates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYear\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of Burkitt\u0026rsquo;s Lymphoma cases admitted\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal Admissions\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIncidence rate per 100,000 admissions\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIncidence rate per 100,000 of the catchment population\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1990\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2395\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1991\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3549\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1992\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2949\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1993\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3127\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e95.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 204.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-4.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1994\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e169.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(43.97, 295.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-7.17\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1995\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3747\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e80.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 170.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-3.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1996\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4114\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e72.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 155.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-3.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1997\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e69.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(-0, 148.57)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-3.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4182\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e191.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(58.74, 323.86)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-7.32\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e39.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 93.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-2.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e117.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(23.42, 210.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-5.60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e196.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(74.56, 317.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.08\u0026ndash;7.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2002\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4797\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e145.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(37.81, 253.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-5.92\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5459\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e109.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(21.96, 197.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-5.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4963\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e80.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(1.61, 159.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-3.90\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4612\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e173.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(53.28, 293.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-6.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4819\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e145.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(37.68, 252.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-5.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e234.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(89.22, 380.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-7.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e49.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 119.04)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-2.34\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4429\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 107.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-2.12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3982\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2687\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3932\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 75.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-1.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 72.27)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-1.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3660\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 80.83)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-1.37\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2187\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3752\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00\u0026ndash;0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3327\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(0, 89.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.00-1.08\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn 1990, 847 cases were positive for P. falciparum malaria, out of 2,395 total admissions, resulting in a Falciparum malaria positivity percentage of 35% of all admissions. Overall, in the first epoch (1990\u0026ndash;2000), the number of positive cases and the Falciparum malaria positivity fraction continued to increase, reaching their highest point in 1992, with 1,595 positive cases and a positivity percentage of 54%. The median parasite density in this first epoch was 13,966.5 (IQR 123,910). In the second and third stages, the number of positive cases, total admissions, and positivity percentage decreased, with the lowest values occurring in 2017. The median parasite density also rapidly decreased over the two epochs, being 9,744 (IQR 112440) and 7,224 (IQR 107,634) in the second and third epochs, respectively. The decline across the three epochs was significant (Kruskal‒Wallis chi-square test, 12.3; P\u0026thinsp;=\u0026thinsp;0.0021). This difference was similarly significant when one-way ANOVA was applied (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFinally, to analyze the relationship between endemic Burkitt\u0026rsquo;s lymphoma cases and Falciparum malaria infection point prevalence, linear regression was applied, as displayed in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The correlation coefficient was 0.53, indicating a moderately strong positive correlation (P\u0026thinsp;=\u0026thinsp;0.0024).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMore than 100,000 children are diagnosed with cancer in the sub-Saharan Africa region\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e These estimates are imprecise and grossly underestimate the burden largely because of the underdeveloped healthcare infrastructure across all aspects of cancer management (absent cancer registries, paucity of healthcare professionals trained in cancer diagnosis and management, poor access to treatment, and limited cancer research) in the region\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Overall, mortality is equally high, with a cure rate lower than 50% in many countries\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNon-Hodgkin lymphoma (NHL) is one of the most prevalent childhood cancers in sub-Saharan Africa\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The bulk (more than 50%) of NHLs are composed of BL, and the proportion of BL may exceed 60\u0026ndash;80% within the endemic BL belt\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The endemic BL region generally overlies the Plasmodium malaria-endemic countries in tropical Africa\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Given the consistently documented overlay of the two conditions, repeated P. falciparum malaria infection has been postulated to play a central role in the pathogenesis of endemic BL, resulting in higher incidence rates\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. However, this postulated association has never been fully examined. Therefore, this study is one of the largest and longest observational studies tracking both the incidence rates of endemic BL and P. falciparum malaria infections within the BL region.\u003c/p\u003e\u003cp\u003eAnalysis of the cumulative BL cases over the study period revealed that the median age at presentation was approximately 6.0 years, with an IQR of approximately 3\u0026ndash;8 years for boys and 7.0 (3\u0026ndash;11) years for girls, which is similar to that reported in other studies\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The annual incidence rates were highest in the mid-1990s, at approximately 4.8 per 100,000 of the population at risk, which was within the 3\u0026ndash;6 per 100,000 uniformly documented within the endemic Burkitt\u0026rsquo;s lymphoma belt\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. From the mid-2000s, a gradual decline was recorded, reaching a nadir of 0.2 cases per 100,000 people by the year 2020.\u003c/p\u003e\u003cp\u003eMalaria infections were very common in the first 15 years (1990-2000s), with close to 50% of all admitted children being diagnosed with falciparum malaria clinically as well as through a positive malaria blood smear. From the mid-2000s, the number of malaria-positive cases decreased to less than 20% of all pediatric admissions. This decline was sustained for the remainder of the study period. The year-over-year decline in the percentage of children admitted with malaria was significant (\u003cem\u003eP value\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/em\u003e This significant decline in malaria infections has been documented in other hospitals and community-based studies\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This phenomenon may be driven by a combination of preventive strategies, such as early effective treatment, indoor residue spraying, and the use of long-lasting insecticide-treated mosquito nets.\u003c/p\u003e\u003cp\u003eMalaria parasite density may correlate with population-level variation in infection burden\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, with high malaria prevalence areas tending to be associated with higher parasite density among those infected and vice versa\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In this study, the malaria parasite density closely followed a similar trajectory to that of the malaria-positive fractions. The year-over-year decrease in malaria parasite density across the study period was significant (\u003cem\u003eP value\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/em\u003e Therefore, although this was a hospital-based study, a significant decrease in both the percentage of children admitted with positive malaria slides and malaria parasite density plausibly indicates an equally significant decline in overall P. falciparum malaria prevalence within the catchment population.\u003c/p\u003e\u003cp\u003eFinally, this study examined the correlation between P. falciparum malaria reduction and incidence rates of endemic BL. The correlation coefficient was 0.53, indicating a moderately strong positive correlation (P\u0026thinsp;=\u0026thinsp;0.0024).\u003c/p\u003e\u003cp\u003eSince P. falciparum malaria is postulated to play a crucial role in the pathogenesis of endemic BL, reducing and/or eradicating malaria infection has been advocated as a plausible preventive strategy for endemic BL \u003csup\u003e24\u003c/sup\u003e. However, few studies have explored this relationship, and the uncertainties of any association still abound. Our study, which spans three decades, is one of the first to clearly demonstrate that a sustained reduction in P. falciparum malaria infection was associated with a significant decline in the incidence rates of endemic BL. Notably, a lag of at least half a decade was discernible between the years of noticeable reduction in the malaria positivity fraction and malaria parasite density before any reduction in annual cases of endemic BL was documented. This may imply that seasonal or short-lived variations in malaria incidence or transmission dynamics have negligible impacts on the incidence rates of endemic BL and that sustained reduction is a requirement. Furthermore, although the onset of partial immunity in older children leading to repeated cycles of infections that are cleared without treatment may play a role in the pathogenesis of the malignancy\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, the time it takes for this to \u0026ldquo;\u003cem\u003eunlock\u003c/em\u003e\u0026rdquo; the process leading to B-cell immortalization is unknown. It is therefore possible that the high number of endemic BL cases witnessed during the initial years of malaria infection reduction depicts individuals in whom the pathological process may have started in the earlier years of very high malaria prevalence.\u003c/p\u003e\u003cp\u003eOverall, our study demonstrates the transformation of an endemic BL picture into a level of annual incidence rates similar to those experienced within sporadic BL regions. Previous studies that have examined the relationships between BL and malaria have reported mixed findings. A study conducted in Uganda between 1976 and 2005 concluded that the distribution of Burkitt\u0026rsquo;s lymphoma did not differ across the three decades\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. However, that study was conducted during decades of sustained high malaria prevalence in the region. Therefore, given the postulated role of P. falciparum malaria in this pathogenesis, it is unlikely that a discernible change would have been demonstrated. Another recently published article equally explored global trends in pediatric lymphomas\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. That study noted an increase in BL across 8 of the 15 global regions. However, the study used data collected from 1988\u0026ndash;2012, a period of high sustained malaria transmission\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In summary, the findings of our study are close to what was reported in a publication from Tanzania that utilized data collected between 2000 and 2009\u003csup\u003e27\u003c/sup\u003e. That study revealed that the number of BL cases was greater in the first period (2000\u0026ndash;2004) than in the second period (2005\u0026ndash;2009), although there was uncertainty in the significance of the observed decline\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Notably, the Tanzania study utilized data across a much shorter observation period (one decade). Furthermore, this was conducted during a period of transition from the high malaria incidence and the initial years of declining malaria transmission, which may explain the observed uncertainty.\u003c/p\u003e\n\u003ch3\u003eSignificance of the study findings\u003c/h3\u003e\n\u003cp\u003ePediatric cancers are expensive to diagnose and treat, with the estimated cost per diagnosis of a new single case being more than \u003cspan\u003e$\u003c/span\u003e31,000\u003csup\u003e28\u003c/sup\u003e. With respect to endemic BL, treatment outcomes in sub-Saharan Africa remain suboptimal\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003c/sup\u003e and the cost for treating a single patient is estimated at close to \u003cspan\u003e$\u003c/span\u003e12,829\u003csup\u003e30\u003c/sup\u003e. Although this puts the treatment costs within the boundaries of what would be considered cost effective by various models, including the WHO CHOICE model\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, it is still prohibitive as a direct cost within the fragile healthcare systems in most SSA countries. On the other hand, malaria control programs are among the most cost effective and can be deployed rapidly at scale\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The median financial cost of protecting one person for one year may be well under \u003cspan\u003e$\u003c/span\u003e5 for most of the proven interventions, such as insecticide-treated nets, indoor residue spraying, and intermittent preventive therapy, with a considerable benefit-to-cost ratio\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. Therefore, our study demonstrates that malaria infection control programs may lead to a significant reduction in the burden of endemic BL, and a malignancy that is responsible for 40\u0026ndash;60% of the pediatric cancers within large territories within the endemic BL zone is thus crucial. This finding lends credence to the postulation of the association between BL and P. falciparum malaria as well as suggestions that sustained malaria prevention could be a viable control strategy for this malignancy.\u003c/p\u003e\n\u003ch3\u003eLimitations\u003c/h3\u003e\n\u003cp\u003eFirst, the diagnostic capabilities for cancers in Kenya and other SSA regions\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e are suboptimal, which may result in under diagnosis. Second, there is a paucity of knowledge on community health-seeking behavior for childhood cancers. Myths and misconceptions on the prospects of treatment and outcomes may lead to many children not being brought to formal healthcare systems\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Third, this study was conducted at a single site in one country. The pattern of referral may have changed, although there was no increase in the number of BL cases in adjacent hospitals during this period. Fourth, although the results may be generalizable to other similar regions, multisite and multi-country studies are needed to address this important question equally.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThere has been a significant decrease in the annual incidence rate of endemic BL associated with a sustained reduction in malaria incidence. Importantly, this is the first study to effectively demonstrate such phenomena and hence lends credence to the postulated association between endemic BL and P. falciparum malaria. However, multisite, multi-country studies exploring this topic within the endemic BL belt are needed.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAnalysis of Variance\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBurkitt\u0026rsquo;s lymphoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCGMRC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCentre for Geographic Medicine Research Coast\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eEBV\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEpstein‒Barr virus\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eERC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEthical Review Committee\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHaemoglobin\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInterquartile Range\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eKEMRI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eKenya Medical Research Institute\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eKNH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eKenyatta National Hospital\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eLMICS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eLow- and Middle-Income Countries\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMYC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMyelo-Cytomatosis gene\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNHL\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNon-Hodgkin lymphoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUON\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUniversity of Nairobi\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eUSA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eUnited States of America\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWorld Health Organization\u0026rsquo;s\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003econsiderations\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProspective surveillance (both inpatient and outpatient) focused on describing common childhood illness was instituted at the Kilifi site by Kenya Medical Research Institute (KEMRI) Center for Geographic Medicine Research Coast (CGMRC) from 1989. \u0026nbsp;All Guardians are requested for consent to use the data of admitted children prospectively at the point of admission. This study utilized secondary anonymized data from the site and further individual consent to analyze the data was deemed not necessary. Importantly, studies conducted via KEMRI adhere to internationally accepted norms including the Declaration of Helsinki. Further, this study was approved by Kenyatta National Hospital-University of Nairobi Ethical Review Committee (KNH-UON ERC), approval number \u003cstrong\u003e\u003cem\u003eP298/04/2022\u003c/em\u003e\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors reviewed and approved the final manuscript for publication. No other consent for publication was required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDatasets generated and analyzed during this study are available upon direct request to the corresponding author via the Kenya Medical Research Institute.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests. The views expressed do not necessarily represent the views of the authors\u0026rsquo; affiliated institutions.\u003cbr\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Welcome Trust,\u0026nbsp;grant code (077092/B/05/Z) and Kenya Medical Research Institute. The funder had no role in the study design, data collection, and analysis or manuscript preparation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMKM was the lead author; he oversaw the data collection and analysis and drafted the initial manuscript. SM assisted in data collection and was involved in the review of the final manuscript. FM assisted in the data analysis, drafted the initial manuscript and reviewed the final manuscript. CRN, DCW \u0026amp; NK were involved at various points in the drafting of the manuscript and extensive review of the final submitted manuscript. All the authors reviewed and approved the final manuscript for submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H et al. 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Age, Spatial, and Temporal Variations in Hospital Admissions with Malaria in Kilifi County, Kenya: A 25-Year Longitudinal Observational Study. PLoS Med 13, (2016).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNdlovu SR, Kuupiel D, Ginindza TG. Mapping evidence on the distribution of pediatric cancers in sub-Saharan Africa: A scoping review protocol. Syst Rev. 2019;8:1\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSinfield RL, et al. Spectrum and presentation of pediatric malignancies in the HIV era: experience from Blantyre, Malawi, 1998\u0026ndash;2003. Pediatr Blood Cancer. 2007;48:515\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOgwang MD, Bhatia K, Biggar RJ, Mbulaiteye SM. Incidence and geographic distribution of endemic Burkitt lymphoma in northern Uganda revisited. Int J Cancer 123, (2008).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNoy A. Burkitt Lymphoma \u0026mdash; Subtypes, Pathogenesis, and Treatment Strategies. Clin Lymphoma Myeloma Leuk 20, (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMayengue PI, et al. Variation of prevalence of malaria, parasite density and the multiplicity of Plasmodium falciparum infection throughout the year at three different health centers in Brazzaville, Republic of Congo. BMC Infect Dis. 2020;20:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePeprah S et al. Risk factors for Burkitt lymphoma in East African children and minors: A case\u0026ndash;control study in malaria-endemic regions in Uganda, Tanzania and Kenya. Int J Cancer 146, (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKamulegeya A, Muwazi L, Kasaganki A, Rwenyonyi CM, Kuteesa A. Trends in Burkitt\u0026rsquo;s lymphoma: A three-decade retrospective study from Uganda. Oral Surg. 3, (2010).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChun GYC, Sample J, Hubbard AK, Spector LG, Williams L. A. Trends in pediatric lymphoma incidence by global region, age and sex from 1988\u0026ndash;2012. Cancer Epidemiol. 2021;73:101965.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAka P et al. Incidence and trends in Burkitt lymphoma in northern Tanzania from 2000 to 2009. Pediatr Blood Cancer 59, (2012).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGithang\u0026rsquo;a J, et al. The cost-effectiveness of treating childhood cancer in 4 centers across sub-Saharan Africa. Cancer. 2021;127:787\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOzuah NW, Lubega J, Allen CE, El-Mallawany NK. Five decades of low intensity and low survival: Adapting intensified regimens to cure pediatric Burkitt lymphoma in Africa. \u003cem\u003eBlood Advances\u003c/em\u003e vol. 4 at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1182/bloodadvances.2020002178\u003c/span\u003e\u003cspan address=\"10.1182/bloodadvances.2020002178\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDenburg AE, et al. The cost effectiveness of treating Burkitt lymphoma in Uganda. Cancer. 2019;125:1918\u0026ndash;28.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eConteh L, et al. Costs and Cost-Effectiveness of Malaria Control Interventions: A Systematic Literature Review. Value Health. 2021;24:1213\u0026ndash;22.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBoyle P, Ngoma T, Sullivan R, Brawley O. Cancer in Africa: The way forward. Ecancermedicalscience 13, (2019).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRenner LA, McGill D. Exploring factors influencing health-seeking decisions and retention in childhood cancer treatment programmes: perspectives of parents in Ghana. Ghana Med J 50, (2016).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7539041/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7539041/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eBurkitt\u0026rsquo;s lymphoma (BL) is a type of non-Hodgkin lymphoma that may account for more than 40% of childhood malignancies in tropical Africa. The endemic version is common in equatorial Africa, where a BL belt has been mapped. The role of P. falciparum malaria infection in BL has been postulated but not substantiated. The decrease in P. falciparum malaria infection offers an opportunity to examine this association.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eIn this study, we utilized data collected over three decades (1990\u0026ndash;2020) and examined the trends in annual admission incidence rates of Burkitt\u0026rsquo;s lymphoma among pediatric admissions (0\u0026ndash;14 years) in relation to the reduction in malaria admissions.\u003c/p\u003e\u003ch2\u003eFindings:\u003c/h2\u003e\u003cp\u003eNinety-five patients with Burkitt\u0026rsquo;s lymphoma were identified, of whom 72 (75.8%) were male. During the first epoch (1990\u0026ndash;1999) and second decade, 29 cases and 62 cases were diagnosed, resulting in 10-year cumulative incidence rates of 93.1 cases and 130.3 cases per 100,000, respectively. In the third decade, 2010\u0026ndash;2019, there were only 4 cases (cumulative incidence of 10.2 cases per 100,000). With one-way ANOVA, the F statistic for within- and between-group comparisons was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), indicating that the decline across the three epochs was statistically significant. Similarly, the median parasite density decreased from 13,966.5 (interquartile range (IQR) 123,910) in the first epoch to 7,224 (IQR 107,634) in the third epoch (Kruskal‒Wallis chi-square test, 12.3; P\u0026thinsp;=\u0026thinsp;0.0021). One-way ANOVA for within- and between-group comparisons was equally significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The correlation coefficient between endemic BL and P. falciparum malaria infection was 0.53, indicating a strong positive correlation (P\u0026thinsp;=\u0026thinsp;0.0024), implying that as P. falciparum malaria infection decreased, the endemic BL incidence rate decreased.\u003c/p\u003e\u003ch2\u003eInterpretation:\u003c/h2\u003e\u003cp\u003eThere has been a significant reduction in the annual incidence rates of Burkitt\u0026rsquo;s lymphoma in the coastal region of Kenya. It is plausible that this decrease can be explained by an equally sustained and significant decline in the number of falciparum malaria infections.\u003c/p\u003e","manuscriptTitle":"A “Familiar Foe Revisited\": Examining the Relationship between endemic Burkitt’s Lymphoma and Changing Malaria Admissions in The Coastal Region of Kenya","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-29 15:08:34","doi":"10.21203/rs.3.rs-7539041/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-12T15:39:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-11T10:40:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"173563705787897402528380763961977979055","date":"2025-11-06T15:30:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"15899196688351479074910781520730582872","date":"2025-11-04T06:19:09+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-26T09:25:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"168423105795121377812213669699181709067","date":"2025-10-21T11:02:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"88558152779100244530540748090149879241","date":"2025-10-21T00:10:53+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-18T09:14:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-18T09:13:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-09-15T18:44:31+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-13T20:13:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-09-13T20:09:50+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"73c443f9-4340-4e1f-b4c4-f24fcbb06e7f","owner":[],"postedDate":"September 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-22T16:08:48+00:00","versionOfRecord":{"articleIdentity":"rs-7539041","link":"https://doi.org/10.1186/s12885-025-15450-9","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-12-18 15:58:11","publishedOnDateReadable":"December 18th, 2025"},"versionCreatedAt":"2025-09-29 15:08:34","video":"","vorDoi":"10.1186/s12885-025-15450-9","vorDoiUrl":"https://doi.org/10.1186/s12885-025-15450-9","workflowStages":[]},"version":"v1","identity":"rs-7539041","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7539041","identity":"rs-7539041","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}