Misdiagnosis of Dengue Fever and Co-infection With Malaria and Typhoid Fevers in Rural Areas in Southwest Nigeria

Okoror, Lawrence Ehis; Bankefa, Emmanuel Olufemi; Ukhureigbe, Oluchi Mariam; Ajayi, Evelyn Olubunmi; Ojo, Stephen K.S.; Ogeneh, Bryan O.

doi:10.21203/rs.3.rs-292692/v1

Cited by 5 publications

(6 citation statements)

References 17 publications

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“…To better understand the real challenges, data from resource-constrained settings are needed 11 . Utmost the reliance of diagnosis on the Widal test would also give a hyperbolic burden 9,12,17,18,31 , and overtreatment of suspected cases 14,17,31,38 which may led to ever-increasing drug resistance in the near future 12,17,21,24,31 .…”

Section: Discussionmentioning

confidence: 99%

“…This is due to the poor laboratory infrastructures, and the cost unaffordability of culture-based diagnosis in Ethiopia 13,17 .The Widal test is limited to differentiate the overlapping symptoms from other acute febrile illnesses such as malaria and viral enteritis 6,18,19 . The false positivity of the Widal test for febrile illness would complicate and worsen the malarial and viral febrile illness 20,21 . The Widal test-based studies displayed exaggerated findings of…”

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confidence: 99%

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Rapid stool antigenic test for typhoid fever among suspected cases, Northeast, Ethiopia

Geteneh

Tadesse

Biset

et al. 2023

Sci Rep

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Typhoid fever continued to be the key cause of morbidity and mortality in developing countries with poor hygienic practices and limited access to safe drinking water. The Widal card agglutination test is the main diagnostic tool in Ethiopia, which is limited in differentiating the overlapping symptoms with other acute febrile illnesses such as malaria and viral enteritis. This eventually leds to unnecessary antibiotic use and eventual drug resistance. Therefore this study wants to assess the burden and associated potential risk factors of typhoid fever among suspected cases using the typhoid rapid stool antigen test in Northeast Ethiopia. A hospital-based cross-sectional study was conducted at Gaint and Meket Shediho primary hospitals from May to July 2021. A total of 255 patients clinically suspected of typhoid fever, and willing to grant informed consent were included systematically. The demographic and hygiene-related variables were collected using a pre-tested structured questionnaire. The rapid stool antigenic test and xylose-lysine-deoxycholate agar (XLD) stool culture were evaluated for the level of agreement. The present study indicated that the prevalence of typhoid fever was 15.3%. This displayed that the human-restricted infectious disease, typhoid fever remained a challenge to Ethiopians. Washing hands with soap, history of typhoid fever, having previous history of hospitalization, and chronic underlying disease was the significant potential factor for typhoid fever. The higher agreement of the rapid stool antigenic test with the stool culture can indicate the factual burden of typhoid fever in the suspected population. This could minimize empiric treatment and the possible emergence of drug resistance. Thus, resource-poor settings may need to look for a rapid and reliable stool antigenic test.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Rapid stool antigenic test for typhoid fever among suspected cases, Northeast, Ethiopia

Geteneh

Tadesse

Biset

et al. 2023

Sci Rep

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“…Although there were numerous reports of isolated outbreaks in Nigeria after 1960 (Table 1), many of the outbreaks were likely unreported, unidentified, or neglected due to a lack of diagnostic tools and uninformed health professionals in medical facilities about the disease [19]. Additionally, most cases of dengue fever are misdiagnosed as malaria or typhoid fever in most healthcare facilities [20]. In Nigeria, dengue fever is endemic in almost all states and may be the leading cause of unclassified febrile illness [21].…”

Section: N Results and Discussionmentioning

confidence: 99%

Addressing the Dengue fever challenges in Nigeria: A narrative review and recommendations for control

2024

Infez Med

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Dengue fever is a mosquito-borne viral infection that continues to pose a significant public health threat globally, including Nigeria. Here, we provided a review of dengue fever outbreaks in Nigeria from 1972 to 2023, examining the epidemiology, prevention strategies, challenges faced in combating the disease, and recommendations to mitigate its spread and transmission. We utilized scholarly databases such as PubMed and Google Scholar in writing this paper. The search keywords like, "dengue fever", "break-bone fever", "dengue fever virus" "outbreak", "Nigeria", "prevalence", and "epidemiology", were used to get appropriate published articles about the subject areas. Over the past five decades, Nigeria has experienced intermittent outbreaks of dengue fever, with varying degrees of severity and geographic distribution. Factors such as urbanization, climate change, and inadequate healthcare infrastructure have contributed to the resurgence and spread of the disease in the country. De-spite efforts to control dengue transmission through vector control measures and public health interventions, challenges persist, including limited surveillance capacity, diagnostic delays, and gaps in vector control strategies. The emergence of new dengue virus serotypes and the potential for co-circulation with other arboviruses further complicate control efforts. This review highlights the importance of strengthening surveillance systems, enhancing vector control measures, improving diagnostic capabilities, and increasing public awareness to effectively mitigate the burden of dengue fever in Nigeria. Collaboration between government agencies, healthcare providers, researchers, and international partners is crucial in addressing the growing threat of dengue fever and reducing its impact on public health in Nigeria.

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“…However, case data can be easily biased by changes in case definitions or reporting practices (8,20), which can cause artificial fluctuations in Rt estimates, and there is no data to examine disease dynamics prior to the first case observation (whereas phylogenetic tree data can be used to reconstruct past pathogen dynamics). Furthermore, viruses that can cause similar clinical symptoms (such as Zika, chikungunya and dengue viruses (21,22)) can be easily misreported where specific molecular or serological testing is not conducted. This can result in the inferred Rt capturing the average population dynamics of multiple cocirculating pathogens, which is less useful to inform disease-specific control measures such as vaccination programs (23)(24)(25).…”

Section: Introductionmentioning

confidence: 99%

EpiFusion: Joint inference of the effective reproduction number by integrating phylodynamic and epidemiological modelling with particle filtering

Judge,

Vaughan,

Russell

et al. 2023

Preprint

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Accurately estimating the effective reproduction number (Rt) of a circulating pathogen is a fundamental challenge in the study of infectious disease. The fields of epidemiology and pathogen phylodynamics both share this goal, but to date, methodologies and data employed by each remain largely distinct. Here we present EpiFusion: a joint approach that can be used to harness the complementary strengths of each field to improve estimation of outbreak dynamics for large and poorly sampled epidemics, such as arboviral or respiratory outbreaks, and validate it for retrospective analysis. We propose a model of Rt that estimates outbreak trajectories conditional upon both phylodynamic (time-scaled trees estimated from genetic sequences) and epidemiological (case incidence) data. We simulate stochastic outbreak trajectories that are weighted according to epidemiological and phylodynamic observation models and fit using particle Markov Chain Monte Carlo. To assess performance, we test EpiFusion on simulated outbreaks in which transmission and/or surveillance rapidly changes and find that using EpiFusion to combine epidemiological and phylodynamic data maintains accuracy and increases certainty in trajectory and Rt estimates, compared to when each data type is used alone. Finally, we benchmark EpiFusion’s performance against existing methods to estimate Rt and demonstrate advances in efficiency and accuracy. Importantly, our approach scales efficiently with dataset size, including the use of phylogenetic trees generated from large genomic datasets. EpiFusion is designed to accommodate future extensions that will improve its utility, such as introduction of population structure, accommodations for phylogenetic uncertainty, and the ability to weight the contributions of genomic or case incidence to the inference.Author SummaryUnderstanding infectious disease spread is fundamental to protecting public health, but can be challenging as disease spread is a phenomenon that cannot be directly observed. So, epidemiologists use data in conjunction with mathematical models to estimate disease dynamics. Often, combinations of different models and data can be used to answer the same questions – for example ‘traditional’ epidemiology commonly uses case incidence data (the number of people who have tested positive for a disease at a certain time) whereas phylodynamic models use pathogen genomic sequence data and our knowledge of their evolution to model disease population dynamics. Each of these approaches have strengths and limitations, and data of each type can be sparse or biased, particularly in rapidly developing outbreaks or lower-middle income countries. An increasing number of approaches attempt to fix this problem by incorporating diverse concepts and data types together in their models. We aim to contribute to this movement by introducing EpiFusion, a modelling framework that makes improvements on efficiency and temporal resolution. EpiFusion uses particle filtering to simulate epidemic trajectories over time and weight their likelihood according to both case incidence data and a phylogenetic tree using separate observation models, resulting in the inference of trajectories in agreement with both sets of data. Improvements in our ability to accurately and confidently model pathogen spread help us to respond to infectious disease outbreaks and improve public health.

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Misdiagnosis of Dengue Fever and Co-infection With Malaria and Typhoid Fevers in Rural Areas in Southwest Nigeria

Cited by 5 publications

References 17 publications

Rapid stool antigenic test for typhoid fever among suspected cases, Northeast, Ethiopia

Rapid stool antigenic test for typhoid fever among suspected cases, Northeast, Ethiopia

Addressing the Dengue fever challenges in Nigeria: A narrative review and recommendations for control

EpiFusion: Joint inference of the effective reproduction number by integrating phylodynamic and epidemiological modelling with particle filtering

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