Background: We aimed at investigating the impact of malaria on the haematological parameters of residents from different demographic settlements in the Ashanti Region of Ghana. Malaria parasites trigger changes in certain haematological parameters, which may result in a number of clinical manifestations. Differences in demographic settlements, such as rural, peri-urban and urban settlements may also influence these changes, but this has not been extensively studied in Ghana.Methods: We conducted a hospital-based, cross-sectional study from January to December 2018 in three different settlements. A total of 598 participants were recruited. Blood smears were examined to detect and quantify malaria parasitaemia, while haematological parameters were measured using a haematology analyser.Results: Participants from the rural settlement had the highest malaria prevalence (21.3%) compared to urban (11.8%) and peri-urban areas (13.3%); however, the peri-urban area had the highest median parasite density . Age was significantly associated with the odds of malaria positivity . When haematological parameters of the malaria-infected study participants were compared to the parameters of uninfected participants, red blood cell count (p=0.017), haemoglobin (p=0.0165), haematocrit (p=0.0015), mean corpuscular volume (p=0.0014), plateletcrit (p<0.0001) and platelet count (p<0.0001) were all significantly lower in the malaria infected group. In addition to age, haemoglobin and plateletcrit levels were also inversely correlated with the odds of testing positive for malaria, suggesting that children who were anaemic and/or thrombocytopaenic were likely to be infected. After fitting the data to a logistic regression model comprising the three variables, the model correctly categorised 78% of uninfected study participants, but only 50% of the malaria-positive participants.Conclusions: Study participants who were positive for malaria were younger and had low haemoglobin and plateletcrit levels compared to uninfected individuals. Further studies are needed to more precisely elucidate the relationship between malaria infection,demographic and haematological parameters. Despite the decrease in incidence of mortality due to malaria in the last decade, the most recent World Malaria Report revealed that 228 million clinical cases of malaria were reported, resulting in no less than 405,000 deaths, the majority of which were in sub-Saharan AfricaAnopheles mosquito triggers changes in several host haematological parameters, many of which play a role in malaria pathogenesis. These changes may subsequently affect the general physiology of the host, resulting in a number of clinical manifestations, with anaemia and thrombocytopaenia being the most common. Haematological parameters that are often affected include the relative numbers of circulating cell types such as erythrocytes, platelets, granulocytes and lymphocytes, as well as parameters like haemoglobin concentration4. While erythrocyte and platelet levels are consistently decreased in malaria-infected individuals, there have been conflicting reports on the effect of malaria on leukocyte counts. A recent study showed a significant reduction in leukocyte, as well as platelet and erythrocyte levels in malaria-infected study participants compared with their uninfected counterparts5. Moreover, Kotepuiet al. (2014) reported that low platelet, white blood cell (WBC) and lymphocyte counts were important predictors of malaria infection and, when used with other clinical methods, could improve malaria diagnosis and treatment6. However, another study reported elevated leukocyte levels in malaria-infected study participants compared to their uninfected counterparts, suggesting that the relationship between malaria and certain immunohaematological parameters may be more complex than previously thought7.The introduction of malaria parasites into the host peripheral blood by an infected female9, it is possible that factors such as differences in demographic settlements could also influence observed changes. However, there is relatively limited data on the differences in haematological indices of malaria-infected people in rural, peri-urban and urban settlements, especially in the forested zones. The aim of this study was to investigate the haematological indices of malaria-infected individuals across these different settlements.While haematological changes associated with malaria have been well-characterizedWe carried out a cross-sectional study targeting hospital attendees. In order to avoid bias and avoid including only ‘sick' or symptomatic participants, we extended our sampling to include ‘healthy' participants who accompanied their relatives or friends to the hospital.The protocol for data collection was reviewed and approved by the Committee on Human Research Publication and Ethics of the Kwame Nkrumah University of Science and Technology (CHRPE/KNUST) and the Komfo Anokye Teaching Hospital (CHRPE/KATH), (Ref: CHRPE AP/018/18). All study participants provided written informed consent prior to study enrolment, with parental or guardian consent obtained for children.11.The study was conducted concurrently at the Kumasi South Hospital (KSH), the Kuntanase Government Hospital (KGH) and the Agona Government Hospital (AGH) in the Ashanti region of Ghana. KSH is located in Atonsu, a suburb of Kumasi, the regional capital and second largest city in Ghana, and served as the urban site. KGH is situated in Kuntanase, the capital of the Bosomtwe district. The Bosomtwe district is one of the 27 districts in the Ashanti region and is located approximately 28 kilometres from Kumasi. AGH is in the Sekyere East district and is located approximately 37 kilometres away from Kumasi. KGH and AGH served as the peri-urban and rural study sites, respectively. The urban, peri-urban and rural sites served as proxies for high, medium and low transmission transects. People in the Agona area receive over 11,000 mosquito bites annually, with 800 of them being infectious bites, while people in the Kumasi area receive approximately 400 bites and around 200 infectious bites per year. The transmission intensity in the Kuntanase area is between these twon is the sample size,z is the critical value of the standard normal distribution at 5% level (1.96),p is the estimated malaria prevalence,q = 1 –p andd is the precision level. The prevalence of malaria had previously been determined by Paintsilet al. (2019) to be about 26%12.The sample size was determined using the binomial model. Confidence intervals of 95% and a precision level of 5% was used. In the equation below,Extended data13. An interpreter was employed to translate the written document into the local dialect (Akan) for those who could not read. In addition, thumbprints were obtained for those who could not sign/write. Demographic data such as age, gender and insecticide-treated net (ITN) use were obtained from participants using a semi-structured questionnaire, a copy of which is provided asExtended data13.The minimum sample size required was calculated to be 295; however, we sampled 601 participants to make up for the different transmission seasons (January to December 2018) across which samples were collected. The study targeted people accessing healthcare at the various hospitals. This included patients referred to the laboratory for malaria tests and accompanying caregivers who were not sick. The purpose of the study was explained to potential participants using a participant information leaflet to seek their informed consent, a copy of which is provided asPeople who were critically ill  and those who declined to consent were excluded from the study. Infants under six months (<6 months) were also excluded.From each participant, 2 ml of venous blood was drawn by a trained phlebotomist in the hospital laboratory. This was transferred into an EDTA tube with a unique participant identifier. The blood sample was used to prepare thin and thick films for microscopic examination and automated complete blood counts (CBCs). Blood parameters were estimated using the Sysmex XP-300 Automated Haematology Analyzer. The cell counter provided data on red blood cell (RBC) count, haemoglobin (Hb) level, mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH) level, WBC, lymphocyte, neutrophil, platelet counts, mean platelet volume (MPV), plateletcrit and the red blood cell distribution width (RDW).From the EDTA-treated blood, 6 µL and 3 µL were used to prepare thick and thin blood films, respectively. After air-drying, the thin blood smears were fixed with methanol and both smears subsequently stained with 10% Giemsa for 15 minutes. Two experienced microscopists independently examined the slides under ×100 oil immersion to determine the presence or absence of malaria parasites. Parasites were quantified after counting 200 or 500 WBCs. Parasite densities were calculated as parasite per microliter of blood . A slide was only declared negative when no malaria parasite was seen after scanning 100 high power fields (HPFs).The data were gathered by the authors using standardized questionnaire. At the end of each day, all researchers came together to check the completeness of each individual questionnaire and match them to the lab specimens taken. Prior to the survey we had pre-tested the questionnaire in a community setting to ensure that people understood the questions. Feedback were used to improve the questionnaire before the actual survey was carried out.glm function in R-3.6.214. Results were considered statistically significant ifp ≤ 0.05.The data collected were coded and entered into Microsoft Excel 2016. The data were checked for completeness. Samples with missing data were excluded from the analysis. Thus, three samples with missing microscopy data were excluded completely from all analyses. Data analysis was performed using GraphPad Prism v6 . Data normality was checked using the Shapiro-Wilk normality test. For normally distributed data, comparisons were carried out using one-way ANOVA, whilst data not conforming to the normal distribution were compared using the Kruskal-Wallis or Mann-Whitney Tests. Pairwise multiple comparison across communities was done using Dunn’s multiple comparison test. For the logistic regression analyses, 19 samples were excluded due to incomplete data, bringing the sample count to 579. The regression analyses were carried out using theIn total, 598 participant samples were examined for parasite prevalence and density. A further 19 samples were excluded from the haematological analysis because the haematological indices could not be determined.n=451) were female13. The overall median age was 27 years (IQR=19–40) and there was a statistically significant difference in the age profiles of participants from the three study sites . Study participants in the rural area were comparatively younger, with a median age of 24.5 years (IQR=14–35), followed by those in the peri-urban area, with a median age of 27 years (IQR=19.5–41.5) and finally those in the urban area, with a median age of 29 years (IQR=22.5–43.0). This observation is consistent with expectations as, typically, the youth tend to leave their rural communities in search of jobs as they get older.Out of the 598 samples analysed in the study, 75.4% (n=93) of the study participants hadPlasmodium falciparum infection, confirmed by microscopy. Children between the ages of six and 14 (inclusive) recorded both the highest rates of malaria prevalence (34.8%) and the lowest rates of ITN usage (28.9%) while children less than five years constituted the majority of those who slept under insecticide-treated mosquito nets (58.9%). There was a significant difference in the median parasite densities of infected study participants across the different age groups . Children under five years harboured the highest number of parasites, with a median parasite density of 665(IQR=327–1038), followed by children 6–14 years, with a median density of 504 (IQR=160–4139), and study participants ≥15 years, with a median density of 24.5 (IQR=13–40). Study participants from the urban area reported the highest ITN usage , with people from the peri-urban  and rural areas  reporting slightly lower percentages of usage (p=0.7932). In this case, however, the highest malaria prevalence was recorded in rural inhabitants , followed by the peri-urban area , with the urban centre recording the lowest prevalence . There was also a significant difference in the parasite densities of infected participants across the three communities . Study participants in the peri-urban area recorded the highest median parasite density , followed by the rural area , with the urban area recording the lowest median parasite density  (16% (–311.5) .p ≤ 0.25. All the demographic predictors passed this threshold with the exception of ITN usage (p=0.838), which was subsequently discarded. The remaining variables were used to create a multivariate logistic model, with age emerging as the only significant predictor of infection status , Hb (p=0.0165), haematocrit (p=0.0015), MCV (p=0.00139), platelets (p<0.0001) and plateletcrit (p<0.0001) compared to malaria-negative individuals , haemoglobin level (p=0.046) and plateletcrit (p=0.0001) as being significantly inversely associated with malaria positivity (eβ) produces the odds ratio associated with unitary increments of the variable.To determine key predictors of infection status, we created multivariate models using the six significant haematological parameters fromitivity . As all 15, while thrombocytopaenia is defined as platelet count<150×103/μL16. 48.4% (n=45/93) of all malaria-infected individuals in this study were anaemic compared to 33.3% (n=164/492) of the control group (p=0.0054), with two malaria-infected participants matching the criteria for acute anaemia. In addition, 58.1% (n=54/93) of participants from the infected group were thrombocytopaenic.Anaemia and thrombocytopaenia comprise two of the most common complications associated with malaria. Anaemia and acute anaemia are defined as having Hb levels <11g/dl or <5g/dl, respectivelyp>0.21) that balanced model sensitivity with specificity, and made our predictions based on this threshold. The model correctly identified 78.4% of malaria-negative individuals but only 50% those who were positive , we first defined a decision threshold 4 and decreased (leucopaenia)7 WBC levels in malaria-infected individuals. The present study did not observe any significant changes in the WBCs levels of participants with malaria compared to the uninfected group. One of the most striking results from the study was the low levels of platelet and plateletcrit  observed in malaria-infected study participants compared to uninfected participants, a finding that is consistent with results from other studies16. This observation is particularly common inPlasmodium falciparum30 andPlasmodium vivax infections32. In this present study, 58.1% of malaria-infected individuals were thrombocytopaenic. There are several hypotheses about the reduction of platelets during malaria infection. This abnormality may be the result of blood clots developing in the bloodstream, thereby blocking small blood vessels. The intermittent clotting subsequently depletes the number of circulating platelets in the bloodstream33. The reduction in platelet levels may also be attributable to an immune-mediated mechanism, whereby specific immunoglobulin G (IgG) produced as a result of the parasite invasion, forms a complex with parasite antigens. The resulting complex then binds to and damages platelets, with damaged platelets subsequently removed from circulation34. Ultimately, plateletcrit was the strongest predictor of infection status, with 99.4% increased odds of being malaria-positive for each unit increase in plateletcrit levels. In spite of this, the full predictive model performed rather poorly as only 50% of infected individuals were correctly classified as such. Further studies are needed to more precisely elucidate the relationship between malaria infection status and various host demographic and haematological parameters. Limitations of this study included a skewed gender-balance and a lack of information on recent medical histories as there are many other diseases and conditions that may affect haematological values and could potentially affect the interpretation of the results.Consistent with findings from other studiesd group ; howeverhttps://doi.org/10.7910/DVN/NGBMZM13Harvard Dataverse: Replication Data for: Impact of malaria on haematological parameters of urban, peri-urban and rural patients in the Ashanti region of Ghana.This project contains the following underlying data:- Combined data.xlsx - Combined Data_Age.tab - Malaria Infected population.xlsx - Malaria Uninfected.xlsx - Peri-Urban population.xlsx - Rural population.xlsx - Urban population.xlsx - Data Dictionary.xlsxhttps://doi.org/10.7910/DVN/NGBMZM13Harvard Dataverse: Replication Data for: Impact of malaria on haematological parameters of urban, peri-urban and rural patients in the Ashanti region of Ghana.This project contains the following extended data:- CHRPE Participant Information Leaflet_Malaria.pdf- Questionnaire- Malaria.pdfCreative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).Data are available under the terms of the The authors have made significant improvements based on the last review, but remnants of the requested portions needing review remain. For example, the concluding statement of the abstract is expected to directly respond to the study object of comparing haematological indices across the three sites, but it still reports comparison of infected and uninfected persons. Wherever this infected/uninfected comparison is made, it is not clarified whether it is for the entire data set from the three sites, or a per site analysis. These are minor issues that will greatly enhance the paper as it is.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?PartlyAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?NoAre the conclusions drawn adequately supported by the results?NoAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Immunology of infectious diseases, vaccine discovery and developmentI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Abstract: The following statement; “Age was significantly associated with the odds of malaria positivity ” should have p-value. Despite a narrow confidence interval, the OR is almost 1.0 which suggests that the association cannot be significantly different. Based on table 2, I still recommend to report adjusted OR rather than crude OR which can potentially suffer from bias and confounding.Introduction:two hundred and twenty-eight million clinical cases of malaria were reported, resulting in no less than 405,000 deaths, the majority of which were in sub-Saharan Africa”, the number of cases should be written in figures (i.e 228 million).In the second statement, “Despite the decrease in incidence of mortality due to malaria in the last decade, the most recent World Malaria Report revealed thatMethods:The authors stated that, “Babies younger than six months, patients who were critically ill and those dissenting to give their consent were excluded from the study”. However, babies (<6 months old) are not mentioned in the revised manuscript. This should be corrected.The data, that is to say, the questionnaire were administered by the authors of this article and not by research assistants. Authors are very experienced in conducting similar surveys from different parts of the country and in other research projects. At the end of everyday all researchers came together to check the completeness of each individual questionnaire and match them to the lab specimen taken. Prior to the survey we had pre-tested the questionnaire in a community setting to ensure people understood and that questions were effective. Feedback were used to improve the questionnaire before the actual survey was carried out."I would recommend to add a separate sub-section on collection of demographic data. The details provided in the responses to my previous comments should be summarized and incorporated in the manuscript. “Results:n=66/204), with people from the peri-urban  and rural areas  reporting significantly lower percentages of usage”; please provide a p-value.For the following statement, “Study participants from the urban area reported the highest ITN usage  comparing parameters amongst the three sites. Analysis of the entire data set should follow this format, since comparing the measured parameters across the three transmission zones is what the study set out to do. I see from the tracked changes version that such results comparing the three sites were initially presented, but have now been removed. Knowing which parameters are different in Table 1 will be a useful guide for identifying potential confounders for regression analysis. The analysis should compare the different haematological, demographic and clinical parameters between the three sites. The regression analysis should predict malaria risk using the haematological parameters as independent variables, and correcting for potential confounders such as age and possibly the study site, in order for the analysis to directly answer the research question.Direct comparison of infected with uninfected persons for all data assumes that the different transmission settings will have no impact on outcomes. This analysis should be done per site before combining all data. Also, the table legend describes the study results. The legend should only describe how the information in the table was generated, not the results/data. Kindly remove all results from the legend. Figure 1 legend is a perfect example, with no data in legend, just a description of how the figure was created.Figure 1 needs the horizontal axis title. The vertical axis has parasites/ulIs the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?PartlyAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?NoAre the conclusions drawn adequately supported by the results?NoAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Immunology of infectious diseases, vaccine discovery and developmentI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. We have responded to all the concerns raised by the reviewer. The major changes made in the manuscript are;1. We provide information on the ethical committee and approval number.The Committee on Human Research Publication and Ethics of the Kwame Nkrumah University of Science and Technology and the Komfo Anokye Teaching Hospital (CHRPE/KNUST), reviewed and approved the study protocol (Ref: CHRPE AP/018/18).2. We have re-organized Table 1, which now shows the statistical comparison amongst the three sites for each parameter.3. We have included Figure 1 horizontal axis title.Thank you General comments: The study aimed at assessing haematological changes among malaria patients residing in three different types of settlements. However, the study design and data collection methods could not be tailored to this overall aim. Thus, the manuscript needs major revisions before it can be accepted for publication.Specific comments:Abstract:The design of this study cannot allow to investigate the changes in haematological parameters but rather to assess the status of the parameters at the time of the study. The first statement should be changed to take into account this fact.I would recommend to change the way the results are presented in the abstract:The prevalence of malaria infection in the three settlements should be mentioned.The results of the analyses which compared malaria infected and non-infected patients should state which group had higher or lower haematological values rather that stating that there was a significant difference. This does not provide useful and adequate information to the readers.The results need to be reorganized to provide a more local flow of the findings. It may be useful to first compare all haematological parameters  among infected vs non-infected patients; and then presenting the same values in infected (with or without symptoms) and non-infected asymptomatic patients from the three settlements.  The last statement in the abstract which states that, “Atypical results from routine haematological findings of anaemia and thrombocytopaenia, may be indicative of malaria, …” is not supported by the results presented in the abstract. Furthermore, it is generally known that malaria infection  is associated with anaemia and thrombocytopaenia. This statement needs to be revised, otherwise it can be dropped.Introduction:The authors should use the data presented in the most recent WHO report of 2019, and should also note that the report normally presents data of the past year. For example, WHO report of 2019 contains malaria data of 2018 and not the same year (2019).In the second paragraph, the authors mentioned that infection with malaria parasites trigger haematological changes. Apart from providing some citations, they could not give a brief account of those changes. It is important to provide a reader with the type of changes and the mechanisms associated with such changes.Methods:This was a hospital-based study which targeted patients with symptoms of malaria but later the investigators decided to include asymptomatic relatives. Was this the original plan or it was adopted just to avoid bias?What were the inclusion and exclusion criteria?How were patients sampled and recruited? Did the investigators target all patients attended at the study hospitals?When was the study conducted?Study sites: how and why were sites selected for this study? What criteria were used to select the hospitals?What were the justifications/rationale for using the formula presented on page 3 and malaria prevalence in determining the sample size? I think that the expected differences in haematological parameters among the three settlements should have been taken into account in determining the sample size.How were demographic and clinical data collected? Who collected the data? And what tools were used and how was quality control of the data performed?Since some haematological data are significantly influenced by environment factors  and nutrition, were these data collected? If not, why?I would recommend to re-analyse the data to determine the impact of malaria on haematological parameters by linear/logistic regression or similar analysis to determine the potential contribution of malaria infection on different parameters with adjustment for different co-variates such as age, sex, residence etc.Results:I would recommend presenting a baseline table showing key demographics , prevalence and parasite density in the three study settlements.The results show that 75.5% of the participants were female. Was this deliberately planned to collect more samples from female participants?  Due to the impact of sex on same parameters, this should have been avoided from the study design and sampling.The age differences of participants were also different among participants from the three settlements. This should have also been avoided in the study design in order to get comparable groups.2-test.I would recommend analysing the variations and impact of ITNs, malaria prevalence, age and settlement using logistic regression rather than χThe results comparing different parameters in symptomatic and asymptomatic participants should also be presented.On page 4, the authors stated that they tested for the relationship between anaemia and thrombocytopaenia in malaria-infected patients. However, it is not mentioned in the method how this was done. It is important to have details in the data analysis section to show how the different tests were done.Discussion and conclusion:The authors mentioned that they investigated haematological changes in malaria patients in three settlements. However, the nature and design of this study cannot allow to assess the trends and changes in such parameters, which can better be assessed in a well-designed longitudinal study; with a design such as cohort or case-control study.The differences in haematological parameters reported in both infected and non-infected participants in the three settlements should be thoroughly discussed. The possible explanations for such differences must be provided.The study had many limitations in terms of design (targeted symptomatic patients but later switched to collecting asymptomatic care-givers as well), selection criteria (biased age and sex of patients), lack of data on altitude of residence, socio-economic and nutritional status, and other factors with significant impacts on haematological parameters. These and other limitations need to be well reported and taken into account when drawing the conclusion of the study..Other commentsUnder figure 1, it is mentioned that analysis was done using R software but this was not mentioned in the data analysis section.The authors should revise the document to take care of typos.Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?NoAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?NoAre the conclusions drawn adequately supported by the results?PartlyAre sufficient details of methods and analysis provided to allow replication by others?NoReviewer Expertise:Antimalarial drug resistance and Genomic epidemiology of malariaI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above. Response to reviewers’ commentsAbstract: The design of this study cannot allow to investigate the changes in haematological parameters but rather to assess the status of the parameters at the time of the study. The first statement should be changed to take into account this fact.Response:We appreciate the reviewer’s comment and agree that investigating changes in haematological parameters was outside the scope of this study. We have changed the wording to better reflect the actual aims of the studyThe prevalence of malaria infection in the three settlements should be mentioned. I would recommend to change the way the results are presented in the abstract:We are very grateful for the comments provided by the reviewers of this manuscript. Please see below for our responses.Response: We have now included this information in the abstract.The results of the analyses which compared malaria infected and non-infected patients should state which group had higher or lower haematological values rather than stating that there was a significant difference. This does not provide useful and adequate information to the readers.Response:We have revised the text to include information on which group had higher or lower haematological values.The results need to be reorganized to provide a more logical flow of the findings. It may be useful to first compare all haematological parameters  among infected vs non-infected patients; and then presenting the same values in infected (with or without symptoms) and non-infected asymptomatic patients from the three settlements.Response: We have re-organised the results presented in the abstract to provide a more logical flow of the main findings of the study.The last statement in the abstract which states that, “Atypical results from routine haematological findings of anaemia and thrombocytopaenia, may be indicative of malaria, …” is not supported by the results presented in the abstract. Furthermore, it is generally known that malaria infection  is associated with anaemia and thrombocytopaenia. This statement needs to be revised, otherwise it can be dropped.Response: We have ‘dropped’ the statement in line with the reviewer’s suggestion. Introduction:The authors should use the data presented in the most recent WHO report of 2019, and should also note that the report normally presents data of the past year. For example, WHO report of 2019 contains malaria data of 2018 and not the same year (2019).Response: We have revised the manuscript to reflect the most recent malaria data available from the WHO.In the second paragraph, the authors mentioned that infection with malaria parasites trigger haematological changes. Apart from providing some citations, they could not give a brief account of those changes. It is important to provide a reader with the type of changes and the mechanisms associated with such changes.Response: We have now provided a brief account of the most common haematological changes associated with malaria.Methods:This was a hospital-based study which targeted patients with symptoms of malaria but later the investigators decided to include asymptomatic relatives. Was this the original plan or it was adopted just to avoid bias? Response: The study recruited all study participants at the beginning of the study.What were the inclusion and exclusion criteria?Response: Since the study was carried out in the hospital laboratories, prospective participants were all who had been referred to the hospital laboratory for tests to be conducted, as well as any family members or friends who accompanied them. Babies younger than six months, patients who were critically ill and those dissenting to give their consent were excluded from the study. We have revised the text to make this information clearer.   How were patients sampled and recruited? Did the investigators target all patients attended at the study hospitals?Response: We targeted all patients who had been referred to the hospital’s laboratory, together with any accompanying persons. And of-course only those who gave consent to participateWhen was the study conducted?Response: The study was conducted from January to December 2018.Study sites: how and why were sites selected for this study? What criteria were used to select the hospitals?Response: We selected the hospitals based on our knowledge of the malaria transmission cline. This ranges from,  AGH – moderately high; KGH – moderate; KSH – relatively lowWhat were the justifications/rationale for using the formula presented on page 3 and malaria prevalence in determining the sample size? I think that the expected differences in haematological parameters among the three settlements should have been taken into account in determining the sample size.Response: Unfortunately, there isn’t any prior information on differences in haematological parameters of residents of the three settlements. However, the malaria prevalence used was from a study that sought to predict malaria infection using the haematological parameters of patients from a hospital in a nearby town that can be classified as a peri-urban community. How were demographic and clinical data collected? Who collected the data? And what tools were used and how was quality control of the data performed?Response: The data, that is to say, the questionnaire were administered by the authors of this article and not by research assistants. Authors are very experienced in conducting similar surveys from different parts of the country and in other research projects. At the end of everyday all researchers came together to check the completeness of each individual questionnaire and match them to the lab specimen taken. Prior to the survey we had pre-tested the questionnaire in a community setting to ensure people understood and that questions were effective. Feedback were used to improve the questionnaire before the actual survey was carried out. Since some haematological data are significantly influenced by environment factors  and nutrition, were these data collected? If not, why?Response: We appreciate the reviewer’s comments on altitude and nutrition. However altitude will not be of any effect in our study sites, all of which are between 250m to 300m asl. Unlike the mountainous areas many parts of Kenya and Tanzania, Ghana is relatively flat. We did not collect information on other variable such as nutrition or intestinal helminths and others. We have been studying these communities for a while, we have other studies that focus on nutrition and other infections. However, this study focused on malaria. We do not expect the influence of ‘other environmental’ parameters to significantly differ in the population.I would recommend to re-analyse the data to determine the impact of malaria on haematological parameters by linear/logistic regression or similar analysis to determine the potential contribution of malaria infection on different parameters with adjustment for different co-variates such as age, sex, residence etc.Response: We have re-analysed the data using logistic regression and believe the results are now easier to interpret (Tables 2 & 4). Results:I would recommend presenting a baseline table showing key demographics , prevalence and parasite density in the three study settlements.Response: We appreciate the opportunity to include any additional information that makes our data easier to follow. We have now included a baseline table of demographic information (Table 1).The results show that 75.5% of the participants were female. Was this deliberately planned to collect more samples from female participants? Due to the impact of sex on same parameters, this should have been avoided from the study design and sampling. Response: We appreciate the concern raised by the reviewer. The main aim of the study was to assess the status of the haematological parameters. At the time of recruitment, these were the respondents who agreed to take part in the study after they were taken through the consenting process hence the high numbers of female participants were not deliberately planned. This notwithstanding, we entirely agree that gender category should ideally be as balanced it is practicable.The age differences of participants were also different among participants from the three settlements. This should have also been avoided in the study design in order to get comparable groups.Response: This is a cross sectional study, where individual sent to the lab were approached for consent, we could not discriminate among willing participants. The age groups presented are study participants there were presented at the hospital and consented to participate. That said, future studies will take this into account.I would recommend analysing the variations and impact of ITNs, malaria prevalence, age and settlement using logistic regression rather than χ -test.Response: We are very grateful to the reviewer for this suggestion. We have now re-analysed the data using logistic regression (Tables 2 & 4).The results comparing different parameters in symptomatic and asymptomatic participants should also be presented.Response: The only available infection categories were the malaria-positive and malaria negative groups. We intended to further categorise the study participants into symptomatic and asymptomatic based on temperature readings. Unfortunately, our temperature readings could not reliably distinguish between the two categories. This is a limitation of this study.On page 4, the authors stated that they tested for the relationship between anaemia and thrombocytopaenia in malaria-infected patients. However, it is not mentioned in the method how this was done. It is important to have details in the data analysis section to show how the different tests were done.Response: We have revised this section and completely removed the analysis on the relationship between anaemia and thrombocytopaenia in malaria-infected patients. Discussion and conclusion:The authors mentioned that they investigated haematological changes in malaria patients in three settlements. However, the nature and design of this study cannot allow to assess the trends and changes in such parameters, which can better be assessed in a well-designed longitudinal study; with a design such as cohort or case-control study.Response: We have re-worded the statements to reflect reporting on the status of the hematological parameters, not necessarily the ''changes'.The differences in haematological parameters reported in both infected and non-infected participants in the three settlements should be thoroughly discussed. The possible explanations for such differences must be provided.Response: 2–test.We discuss possible reasons for differences in haematological parameters between all infected and non-infected participants. However, it is now apparent that “settlement” is not significantly associated with malaria positivity. It is, correlated with “age” and this is likely the reason for the positive result using the χThe study had many limitations in terms of design (targeted symptomatic patients but later switched to collecting asymptomatic care-givers as well), selection criteria (biased age and sex of patients), lack of data on altitude of residence, socio-economic and nutritional status, and other factors with significant impacts on haematological parameters. These and other limitations need to be well reported and taken into account when drawing the conclusion of the study.Response: We thank the reviewer for bringing up this very important point. We have added a brief section on the limitations of this study towards the end of the manuscript. However, we maintain that 1. Altitude is not an issue in our study settings at it is in Tanzania and other East African altitudinal transects. The socio-economic and nutritional status are NOT severe confounding factors as in other studies we know they are similar in the populations.Other comments.Under figure 1, it is mentioned that analysis was done using R software but this was not mentioned in the data analysis section.Response: This has been stated appropriately. The authors should revise the document to take care of typos.Response: Typos have been taken care of. et al. assesses malaria-related haematological changes in three different transmission zones and reports statistically significant differences in some of the measured indices between malaria infected and uninfected persons, and higher levels of some indices in infected persons in peri-urban areas compared to levels in persons in the rural and urban areas.The manuscript by Mutala The paper will require some significant revision to better communicate the study findings.Major comments:Authors describe the three study locations as rural, peri-urban and urban. It is unclear from the write up why it is necessary to compare these three demographic settings for haematological differences. If this is being done because of possible differences in transmission intensity however, then it may be more appropriate for the authors to present some current malaria transmission data from these sites and on that basis rather, proceed to refer to these as different transmission intensity settings.Authors should clearly state whether this is a cohort or case control study. Authors should also describe any exclusion criteria that were applied during sampling as the conclusions of the study and potential application of the data may only be valid if certain exclusion criteria were applied. There are some common conditions/infections that could also impact these haematological indices, and without accounting for these, it may not be appropriate to conclude that the observed differences in the indices are due to malaria infection.The manner of results presentation makes comprehension difficult. Authors refer to all 598 participants whose samples were analyzed as patients at some times (second paragraph of the results section), and even though on the basis of the study design, participants can be categorized into those who reported clinically sick, those with asymptomatic infections and those who may be uninfected (by microscopy), no such breakdown in terms of age within these three groups is given in the first subsection of the results. For example, how many of the persons accompanying sick people to the hospital were parasite positive?Most of the subsequent comparisons refer to an infected group and a control group, and it is unclear whether the infected group is in reference to the clinically ill group alone or a combined group of clinically ill and asymptomatic persons. If the latter, what was the reason for combining these two distinct groups as they are likely to have very different haematological profiles?The age range of study participants is not provided. The youngest age groups is given as 0 – 5 years (Table 2).Table 1 seems to be a comparison between infected and uninfected participants from all 3 study sites, but if the goal of the study was to assess differences across different settlements, then why is it relevant to combine data from the three study sites and compare between infected and uninfected persons? A combined presentation of information in Table 1 and Table 3 will be more consistent with the aim of this study, to compare infected and uninfected (maybe sick and not sick rather) for each community.Overall, the data presentation needs to be overhauled. That aside, the presented data does not justify the conclusion that changes in haematological indices can be used as indicative factors for malaria, especially when they depended on the community in which they were measured. I would agree with authors if the indices were consistently different between sick and not-sick persons in all three study sites. Moreover, the unavailability of exclusion criteria in this write up makes it difficult to agree that these observations are due to malaria infections.Minor comments:Abstract, penultimate line before the conclusions section – “…levels amongst patients from urban, …”, not “…between patients…”.“Thrombopaenia”, not “thrombopenia”, to be consistent with all other British spelling of words .Authors should provide the protocol approval number.The statistical analysis section should be updated to reflect the fact that the R software was also used for some graphics .Second sentence of the results section should read: “In total, 598 participant samples…”, not “…participants samples…”.“Kruskal-Wallis”, not “Kruskall-Wallis” .Discussion section, lines 5/6 – which group do the authors refer to as non-malaria patients?Is the work clearly and accurately presented and does it cite the current literature?PartlyIf applicable, is the statistical analysis and its interpretation appropriate?PartlyAre all the source data underlying the results available to ensure full reproducibility?PartlyIs the study design appropriate and is the work technically sound?NoAre the conclusions drawn adequately supported by the results?NoAre sufficient details of methods and analysis provided to allow replication by others?PartlyReviewer Expertise:Immunology of infectious diseases, vaccine discovery and developmentI confirm that I have read this submission and believe that I have an appropriate level of expertise to state that I do not consider it to be of an acceptable scientific standard, for reasons outlined above. We are very grateful to the reviewer, his comments has enabled us clarify and improve the quality of the manuscript. Here we provide point by point response to the comments raised by the reviewer.Major CommentsAuthors describe the three study locations as rural, peri-urban and urban. It is unclear from the write up why it is necessary to compare these three demographic settings for haematological differences. If this is being done because of possible differences in transmission intensity however, then it may be more appropriate for the authors to present some current malaria transmission data from these sites and on that basis rather, proceed to refer to these as different transmission intensity settings.Response:We thank the reviewer for this comment. It makes more biological sense to compare on the basis of transmission. We have provided background information on the malaria transmission intensity and associated references in the manuscript. Whereas people in the Agona area  receive over 11,000 mosquitoe bites with over 800 infectious bites, the Kumasi area receives about 400 bites and about 200 infectious bite per year. The Kuntanase area is moderate in between the two  The citations are below Authors should clearly state whether this is a cohort or case control study. Authors should also describe any exclusion criteria that were applied during sampling as the conclusions of the study and potential application of the data may only be valid if certain exclusion criteria were applied. There are some common conditions/infections that could also impact these haematological indices, and without accounting for these, it may not be appropriate to conclude that the observed differences in the indices are due to malaria infection.Response:We thank the reviewer for bringing up this very important point. This was an observational study with cross-sectional sampling design in which participants were recruited from three hospitals located in different transmission intensity settings. Since participants were recruited from hospitals, we referred to them as “patients”; however, it is now apparent that this term is misleading so we have removed most references to “patients” from the manuscript. We are also aware that many viral and bacterial infections present with malaria-like symptoms, and may also affect haematological indices similarly. This is one of the limitations of our study. The manner of results presentation makes comprehension difficult. Authors refer to all 598 participants whose samples were analysed as patients at some times (second paragraph of the results section), and even though on the basis of the study design, participants can be categorized into those who reported clinically sick, those with asymptomatic infections and those who may be uninfected (by microscopy), no such breakdown in terms of age within these three groups is given in the first subsection of the results. For example, how many of the persons accompanying sick people to the hospital were parasite positive?Response:We have re analysed the data based on reviewer’s comments also echoed by Reviewer 1.We believe the data is now much more clearer to understand. We refer to two categories as malaria infected and not infected due to challenges in distinguishing between symptomatic and asympotmatics earlier described Most of the subsequent comparisons refer to an infected group and a control group, and it is unclear whether the infected group is in reference to the clinically ill group alone or a combined group of clinically ill and asymptomatic persons. If the latter, what was the reason for combining these two distinct groups as they are likely to have very different haematological profiles?Response: The infected group refers to those who tested positive for malaria, regardless of symptoms. We pooled symptomatic and asymptomatic participants together as there was no other way to distinguish between the two groups due to problems with our temperature readings.The age range of study participants is not provided. The youngest age groups is given as 0 – 5 years (Table 2). Response: The age range of study participants has been presented in Table 1. Participants were grouped into three categories: 0—5 years, 6—14 years and 15+ years.Table 1 seems to be a comparison between infected and uninfected participants from all 3 study sites, but if the goal of the study was to assess differences across different settlements, then why is it relevant to combine data from the three study sites and compare between infected and uninfected persons? A combined presentation of information in Table 1 and Table 3 will be more consistent with the aim of this study, to compare infected and uninfected (maybe sick and not sick rather) for each community.Response:We are grateful for this comments from the reviewer to improve our manuscript.2–test. As settlement is no longer a predictor of malaria positivity, we decided to completely remove Table 3.After re-analysing the data using logistic regression, it is clear that “settlement” is not significantly associated with malaria positivity. It is, however, correlated with “age” and this is likely the reason for the positive result using the χOverall, the data presentation needs to be overhauled. That aside, the presented data does not justify the conclusion that changes in haematological indices can be used as indicative factors for malaria, especially when they depended on the community in which they were measured. I would agree with authors if the indices were consistently different between sick and not-sick persons in all three study sites. Moreover, the unavailability of exclusion criteria in this write up makes it difficult to agree that these observations are due to malaria infections.Response:Our data presentation has been ‘overhauled' as recommended by reviewers, data has been re analyzed. Thus the conclusion has been subsequently re-worded and we have included the exclusion criteria in the methods section as requested.Minor comments:Abstract, penultimate line before the conclusions section – “…levels amongst patients from urban, …”, not “…between patients…”. Response:We thank the reviewer for this comment. Sentence corrected as suggested. “Thrombopaenia”, not “thrombopenia”, to be consistent with all other British spelling of words . Response:We thank the reviewer for this observation. The manuscript has been revised to effect these changes.  Authors should provide the protocol approval number. Response:The approval number has been included in the manuscript.The statistical analysis section should be updated to reflect the fact that the R software was also used for some graphics . Response: This has been included in the revised manuscript. Second sentence of the results section should read: “In total, 598 participant samples…”, not “…participants samples…”. Response: The proposed correction has been effected in the manuscript. “Kruskal-Wallis”, not “Kruskall-Wallis” . Response: This correction has been effected in the manuscript. Thank you.Discussion section, lines 5/6 – which group do the authors refer to as non-malaria patients? Response: The sentence has been modified in the manuscript. Abonuusum A, Owusu-Daako K, Tannich E, May J, Garms R, Kruppa T. Malaria transmission in two rural communities in the forest zone of Ghana. Parasitol Res. 2011;108(6):1465‐1471. doi:10.1007/s00436-010-2195-1A.W. Basing∗, S. TayMalaria transmission dynamics of the Anopheles mosquito in Kumasi, Ghana 16th ICID Abstracts / International Journal of Infectious Diseases 21S (2014) 1–460


Febrile illness is the commonest cause of hospitalization in children <5 years in sub-Saharan Africa, and bacterial bloodstream infections and malaria are major causes of death.Plasmodium falciparum parasitaemia and Matrix-Assisted Laser Desorption/Ionization-Time of Flight (MALDI-TOF) to identify bacterial isolates. Disk diffusion method was used for antimicrobial susceptibility testing.From March 2017 to July 2018, we enrolled 2,226 children aged 0–5 years hospitalized due to fever in four major public hospitals of Dar es Salaam, namely, Amana, Temeke, and Mwananyamala Regional Hospitals and Muhimbili National Hospital. We recorded social demographic and clinical data, and we performed blood-culture and HIV-antibody testing. We used qPCR to quantify P. falciparum malaria. Ten children had concomitant malaria and bacteraemia. Gram-negative bacteria (64%) were more frequent than Gram-positive (32%) and fungi (4%). Over 50% of Gram-negative bacteria were extended-spectrum beta-lactamase (ESBL) producers and multidrug resistant. Methicillin resistant Staphylococcus aureus (MRSA) was found in 11/42 (26.2%). The most severe form of clinical malaria was associated with high parasitaemia (>four million genomes/μL) of P. falciparum in plasma. Overall, in-hospital death was 4% , and it was higher in children with bacteraemia  than malaria . Risk factors for death were bacteraemia (p = 0.03), unconsciousness at admission (p < 0.001), and admission at a tertiary hospital (p = 0.003).Nineteen percent of the children  had pathogens detected from blood. Eleven percent  of the children had bacteraemia/fungaemia and 10%  had P. falciparum parasitaemia.Compared to previous studies in this region, our study showed a reduction in malaria prevalence, a decrease in in-hospital mortality, and an increase in antimicrobial resistance (AMR) including ESBLs and multidrug resistance. An increase of AMR highlights the importance of continued strengthening of diagnostic capability and antimicrobial stewardship programs. We also found malaria and bacteraemia contributed equally in causing febrile illness, but bacteraemia caused higher in-hospital death. The most severe form of clinical malaria was associated with  Plasmodium falciparum in plasma samples.Bloodstream infections (BSI) are the commonest causes of hospital admissions and deaths in children in sub-Saharan Africa . Severe Recent efforts in scaling up malaria control programs such as increased use and availability of rapid diagnostic tests (RDT), distribution of free insecticide-treated bed nets, and change to more effective malaria treatment guidelines in sub-Saharan Africa have resulted in a substantial decline of malaria-associated morbidity and mortality .Determining bacterial or fungal infections in BSI is fundamental to management of severe BSI based on etiology. This is challenging in low-income countries because easily available and affordable diagnostic services for BSI other than malaria is limited by both infrastructure and cost . As a reMicrobial etiology of febrile illness varies from bacteria, viruses, parasites, or fungi, between children attending outpatient health care facilities versus in hospitals , and geoP. falciparum malaria.In the Dar es Salaam region of Tanzania, a previous study reported causes of febrile illness among children attending out-patient clinics only . Three oP. falciparum qPCR to quantify parasitaemia and differentiate severe from non-severe clinical malaria, and lastly, the current status of antimicrobial resistance. The present study provides updated information on the contribution of bacteria, fungi, and malaria in severe febrile illness among children admitted in four major hospitals of Dar es Salaam, Tanzania. We also report the risk factors for in-hospital death. In addition, the study shows the association of clinical malaria severity and the levels of P. falciparum parasitemia, using plasma qPCR. We hypothesized that there is widespread antimicrobial resistance in pathogens causing BSI. Our findings showed that there is an increase in the rate of antimicrobial resistance, extended spectrum beta-lactamases, and multidrug resistance. The information will increase clinical awareness of the emerging public health problem of AMR.With the reduction of malaria in mind, information is required, first on the current causes of severe febrile illness and death among hospitalized children, second on the role of ≥37.5°C) at three regional hospitals, Amana, Temeke, and Mwananyamala, and a tertiary hospital, Muhimbili National Hospital (MNH). These are the main public hospitals that serve approximately five million people living in the Dar es Salaam region. The entry point of the study was admission of the patient, and the end point was at discharge of the patient from the hospital, referral to other facilities, and death.This hospital-based cross-sectional study was conducted from March 2017 to July 2018 in Dar es Salaam, Tanzania. The study consecutively included children aged ≤5 years who were hospitalized because of fever  REDCap. Information recorded were date of birth, sex of the child, duration of fever, history and duration of convulsions, vomiting, cough, diarrhea and its duration, antibiotic use during 1 month before the current admission, and history of hospital admissions during the last 6 months. The attending physician performed clinical examination and recorded the following information: level of consciousness, pulse rate, respiratory rate, neck stiffness, irritability, and jaundice. Hemoglobin level was recorded when available. Information was recorded on any antibiotic or antimalarial prescribed by the attending physician, and whether the child had received antibiotics or antimalarials before blood culture was taken. Outcome was recorded as discharged, transferred to another hospital, or died.®  culture system for a maximum of 5 days unless flagged positive earlier. The remaining blood was aliquoted, one portion of whole blood was added to Tempus blood RNA tubes , and the rest if any was centrifuged at 3,000 rpm for 10 min at 4°C to obtain plasma and stored at −80°C until further analysis. Blood remaining after aliquoting was used for HIV rapid testing as per national rapid HIV testing algorithm, SD bioline HIV-1/2 3.0  followed by Uni-GoldTM HIV .A total of 1–5 mL of blood was collected from each child within 24 h of admission. 1–2 mL of blood was inoculated in a pediatric blood culture bottle and incubated at 35°C using the BACTEC 9050Positive blood cultures were sub-cultured on sheep-blood, MacConkey, chocolate, and Sabouraud Dextrose agar (SDA) plates. Standard microbiological methods such as conventional biochemical tests and analytical profile index (API)  were used for identifying bacterial isolates. Fungal isolates that grew on SDA were Gram stained, and for yeast cells germ-tube test was performed. Final identification of both bacterial and fungal isolates was done with MALDI-TOF MS using the Microflex LT instrument and MALDI Biotyper 3.1 software .Staphylococcus aureus isolates were confirmed by the presence of mecA using PCR as previously described (S. aureus and Enterococcus spp. was done using E-test (bioMérieux). Quality control strains were included for all screening tests and PCR.Antimicrobial susceptibility testing was done by disk diffusion technique according to guidelines and breakpoints of the Clinical Laboratory Standards Institute CLSI; . Isolateescribed . ScreeniPathogen Universal Kits (Roche Diagnostics) for total nucleic acid (TNA) were used for extraction of both DNA and RNA from plasma and whole blood, on MagNA Pure 96 instrument . Input volume of plasma and/whole blood was 500 μL, extracted TNA (100 μL) was stored at −80°C.Plasmodium falciparum was detected and quantified using qPCR. The target used for detection of P. falciparum was varATS, using primers, probes, and conditions described previously  and template volume was 4 μL. The final concentration of primer and probe were 800 and 400 nM, respectively. PCR was done using the Light Cycler 480 II Instrument . Each run included a positive control and multiple no-template controls. A plasmid with synthetic varATS insert was included  for PCR and for quantification. DNA quantity for samples with P. falciparum DNA less than the Limit of Quantification (LOQ) was set to be equal to or less than the LOQ (estimated to ≤0.05 genomes/μL). The efficiency (using the formula E = 10–1/slope − 1) was 91.2%, and error value (E) of the assay was 0.012.eviously . Master P. falciparum malaria parasitaemia by qPCR and clinical malaria severity scores was assessed by ANOVA. For all analyses, a P-value of <0.05 was considered statistically significant.Data collected and entered in REDCap was exported to Statistical Package for Social Sciences (SPSS) version 24.0, which was used for data analysis. Categorical data were displayed using frequencies and percentages, and continuous data were displayed using the mean/median and interquartile range (IQR). Chi square and Fischer’s exact test were used to determine association between categorical variables. The risk factors for in-hospital mortality, associations between bacteraemia/malaria, and the demographic/clinical variables were analyzed using univariable and multivariable logistic regression analyses controlling for age and gender of the children. Association between The study included 2,226 children under 5 years of age. Of these 1,299 (58%) were males. The majority of children were below 2 years of age . The mean and median age were 11.09 and 2.04 months, respectively. HIV test results were available for 1,169/2,226 (53%), and 4%  tested positive for HIV. Symptoms among patients with malaria and bacteraemia are shown in Of the 2,226 children admitted with fever, 33.6%  had symptoms representing specific syndromes as follows: gastroenteritis ; meningitis/neck stiffness, 2.7% ; and respiratory tract infection/cough, 20.0% .n = 156, 64%), followed by Gram-positive bacteria (GPB)  and fungi . At least one pathogen was detected in blood from 19%  of the patients. A total of 243 bacteria and fungi were isolated from 236/2,226 children (11%) . The majKlebsiella pneumoniae (42%), Escherichia coli (19%), Pseudomonas spp. (8%), Acinetobacter spp. (8%), Salmonella spp. (6%), Serratia marcescens (5%), Enterobacter cloacae (5%), Alcaligenes faecalis (3%), Pantoea and Providencia spp. (3%), other Gram-negative bacteria  were Proteus mirabilis (n = 2), Brevundimonas diminuta (n = 1), Ralstonia pickettii (n = 1), Microbacterium aurum (n = 1), and Ochrobactrum tritici (n = 1).Gram-negative bacteria isolated were S. aureus (54%), E. faecalis (15%), Enterococcus faecium (23%), S. pneumoniae (4%), and Streptococcus agalactiae (3%) and Enterococcus avium (1%).Gram-negative bacteria isolated were Candida parapsilosis (56%), Candida albicans (22%), and Wickerhamomyces anomalus (22%). In this study we performed single blood culture, therefore we could not confirm coagulase negative Staphylococcus as a cause of the blood stream infection. Coagulase-negative Staphylococcus, Bacillus, and Micrococcus spp. were regarded as likely contaminants and excluded from analysis. These contaminants were found in 4.1% .Fungi isolated were P. falciparum malaria was 10% .Plasma and whole blood samples were available for 1,811 and 252 children, respectively, and total nucleic acid (TNA) was extracted from these 2,063 children. The prevalence of P. falciparum in plasma measured by qPCR (expressed as genomes/μL) was significantly higher in children with 3 or more severity criteria compared to the other groups.To categorize severe and non-severe malaria we used the presence of one or more of the following severity criteria following World Health Organization (WHO) guidelines : jaundicSerratia marcescens (n = 2), K. pneumoniae (n = 2), and one of each of the following bacteria: E. coli, Acinetobacter ursingii, Alcaligenes faecalis, Ochrobactrum tritici, E. faecium, and S. aureus. Of the 10 children with bacteria-malaria co-infection, 40% (4/10) had clinically severe disease and high malaria parasitaemia by qPCR, and one of these four children died.Among children with malaria, 5% (10/204) had co-infection with bacteraemia. Bacteria isolated among these children were Of 2,226 children included, 10%  received anti-malarial treatment and 79%  antibiotic treatment on admission, before blood culture was taken . Of 200 P-value < 0.001, OR 2.81, 95%CI 1.73–4.58). The median age for malaria infection was 27 months. Malaria prevalence was significantly increasing with age, with the highest prevalence (31%) among children older than 25 months . Unconsciousness was also associated with malaria with P value 0.03, OR 1.83, and 95% CI (1.07–3.13). In univariable analysis, severe anemia, convulsions, reduced consciousness, and vomiting were associated with malaria, as shown in P. falciparum. Outcome was not known for 80 children (4%); 58 were referred to a different hospital because their condition worsened, while for 22 children information was not recorded. P-value 0.003; OR 3.68, 95% CI (1.47–9.21).Outcome data were available for 2,146 and 1,988 children tested for bacteraemia/fungaemia and malaria qPCR, respectively. Of 2,146 children, 89 (4%) died while 2,057 (96%) improved and were discharged from the hospital. Of children who died, 25% (22/89) had pathogens detected in blood; 18 had bacteria/fungi and four had P. falciparum genomes/μL , 4/18 (22%), and 2/18 (11%) were infected with Of the 18 children who died, 16 (88%) received antibiotic treatment. Antibiotics prescribed to these children were a combination of either amoxycillin/clavulanic acid or ceftriaxone and gentamicin. Susceptibility testing showed most Gram-negative bacteria were ESBL producers and multi drug resistant (MDR).K. pneumoniae displayed the highest rate of ESBL (90%) followed by E. coli (36%) and other Gram-negative bacteria (14%). Multidrug resistance (MDR), defined as resistance to three or more classes of antimicrobials, was also high (54%) among GNB. MDR among K. pneumoniae, E. coli, and Acinetobacter spp. were 90.3, 36, and 40%, respectively. Gentamicin resistance among GNB was found in 49%. One third of GNB were resistant to ciprofloxacin, and the highest resistance rate(44%) was among K. pneumoniae. Resistance to meropenem was observed in the following isolates of A. baumannii (n = 2) and two isolates of Pseudomonas spp. (n = 2). Like GNB, GPB also displayed high rates of resistance toward different antimicrobial agents. For S. aureus, the prevalence of Methicillin resistant S. aureus (MRSA) was 26%, and MDR was seen in one third of isolates. Enterococcus spp. showed a high rate of MDR of over 80%. There was no vancomycin resistance detected among S. aureus and Enterococcus spp.Antimicrobial resistance pattern among Gram-negative bacteria (GNB) and Gram-positive bacteria (GPB) is shown in In an African setting, identifying etiologies of fever in severe BSI is challenging, first, because of lack of affordable diagnostic tools for conditions other than malaria, and second, fever is a non-specific symptom due to a panoply of conditions. This study demonstrated etiologies of severe febrile illness in 20% of children hospitalized in Dar es Salaam, Tanzania.K. pneumoniae and E. coli were the most common bacteria isolated.The frequent use of antibiotics before specimen for blood culture is taken can likely underestimate the incidence of BSI, especially for fastidious bacteria such as pneumococci, which are susceptible to commonly used antibiotics. In the present study, over three quarters of the children received antibiotics prior to blood culture. This is important to take into account when estimating the relative importance of different infectious agents in severe infections in children. Nevertheless, the prevalence of bacteraemia and fungemia obtained in this study is comparable to what was reported in children in Dar es Salaam (14%) 17 years ago  and in oDar es Salaam is the region of low to moderate malaria endemicity . DespiteP. falciparum genomes in blood and the most severe form of clinical malaria with three or more severity criteria. This concurs with the findings of a multicenter study by P. falciparum in plasma. These findings agree with that of We found significant association between the quantity of P < 0.001) in the same study setting  who received antibiotics on admission did not have growth in blood culture. A high proportion of children were given an antibiotic on admission because the study setting is a low-income country, and availability of laboratory tests such as blood culture to confirm for the bacterial etiology of fever is limited to a few referral hospitals. As a result, initial use of antibiotics following empirical treatment guidelines by the clinicians is difficult to avoid, in an attempt to save lives of children with life threatening severe BSI. This massive use of antibiotics will contribute to increase the existing problem of antimicrobial resistance in this study setting.In the present study the in-hospital mortality was 4%. This is much lower than was reported 17 years ago by This study has some limitations. First, our study was able to identify etiologies of severe febrile illness for only 20% of participants, because viruses and zoonotic bacteria were not investigated for in this study. Viruses were found to be the most common cause of fever in children attending outpatient clinics in Dar es Salaam . WhetherP. falciparum parasitaemia.In summary, compared to previous studies in this region, our study showed a reduction in malaria prevalence, a decrease in in-hospital mortality, and an increase in antimicrobial resistance (AMR) including ESBLs and multidrug resistance. A decrease in mortality may be attributed to the on-going implemented malaria control programs in the country, and the implementation of artemisinin-based treatment regimens may also have contributed. A reduction of congenital HIV may also have contributed to the reduced mortality. An increase of AMR highlights the importance of continued strengthening of diagnostic capability and antimicrobial stewardship programs. We also found malaria and bacteraemia contributed equally in causing febrile illness, but bacteraemia caused higher in-hospital death. The most severe form of clinical malaria was associated with The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.The studies involving human participants were reviewed and approved by the Senate Research and Publications Committee of Muhimbili University of Health and Allied Sciences, National Institute of Medical Research in Tanzania and from the Regional Committee for Medical and Health Research Ethics (REK) in Western Norway. Written informed consent to participate in this study was provided by the participants’ legal guardian/next of kin.P. falciparum. SJM performed statistical analysis and drafted the manuscript. All authors contributed to writing the manuscript and approved the final version.SJM, NL, and BB conceived the study. SJM, NL, BB, JM, NM, SA, and KMa contributed to designing the study. SJM, JM, and NM involved in data collection. SJM and JM performed the microbiological investigations. SJM and KH set up qPCR and analysis for The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Plasmodium falciparum and non-falciparum infections in Ghanaian adults in the Ashanti region during the high transmission season.Ghana is among the high-burden countries for malaria infections and recently reported a notable increase in malaria cases. While asymptomatic parasitaemia is increasingly recognized as a hurdle for malaria elimination, studies on asymptomatic malaria are scarce, and usually focus on children and on non-falciparum species. The present study aims to assess the prevalence of asymptomatic Plasmodium species by rapid diagnostic test (RDT) and polymerase chain reaction (PCR) during the rainy season. Samples tested positive were subtyped using species-specific real-time PCR. For all Plasmodium ovale infections additional sub-species identification was performed.Asymptomatic adult residents from five villages in the Ashanti Region, Ghana, were screened for Plasmodium infection was 284/391 (73%); only 126 (32%) infections were detected by RDT. While 266 (68%) participants were infected with Plasmodium falciparum, 33 (8%) were infected with Plasmodium malariae and 34 (9%) with P. ovale. The sub-species P. ovale curtisi and P. ovale wallikeri were identified to similar proportions. Non-falciparum infections usually presented as mixed infections with P. falciparum.Molecular prevalence of asymptomatic Plasmodium carriers. The high Plasmodium prevalence not detected by RDT in adults highlights that malaria eradication efforts must target all members of the population. Beneath Plasmodium falciparum, screening and treatment must also include infections with P. malariae, P. o. curtisi and P. o. wallikeri.Most adult residents in the Ghanaian forest zone are asymptomatic  The World Health Organization (WHO) aims to achieve a global reduction in malaria case incidence and mortality rates by 90% compared to 2015, elimination in at least 35 countries, and prevention of reintroduction in all malaria-free countries by the year 2030. Although the worldwide burden of malaria substantially decreased since 2010, some high-burden countries in Africa report an increase in malaria cases. According to the WHO, the global targets for 2030 will not be achieved unless there is accelerated change. Ghana belongs to the eleven high-burden countries accounting for > 70% of the global malaria cases and deaths. With an increase of malaria cases by 8%, Ghana is among the two highest burden countries in Africa reporting the highest absolute increase in malaria cases in 2018 compared to 2017  25–44 years). The localization of the study sites in the Asante Akim North district and the range of participants with asymptomatic P. falciparum presented mainly as monoinfection (82%), P. malaria and P. ovale were observed mainly in the context of coinfections with 85% (28/33) and 76% (26/34), respectively. The distribution of Plasmodium infections among different age groups in women and men is demonstrated in Fig. While fection 8%, P. malPlasmodium species in 126 study participants (32%). Adjusted for age, gender and village, the Ct value of the commercial screening PCR was significantly associated with a positive RDT in the whole cohort and in the subgroup with P. falciparum monoinfection  and 96% (102/106). When interpreting very faint bands (n = 17) as positive, sensitivity increased to 48% (136/282) and specificity decreased to 93% (99/106).RDT only detected icipants 2%. AdjusPlasmodium carriage confirmed by PCR were younger on average  compared to participants with negative screening PCR who had a median age of 35 years .Participants with Plasmodium carriage status detected only by PCR in both univariate and multivariate analysis, adjusted for age, gender and village (Table Among the parameters measured by blood count, the platelet count was inversely associated with ge Table . HaemoglPlasmodium infection, with 73% of adult residents being PCR-positive for at least one Plasmodium species. In the studied populations, asymptomatic adults represent a relevant reservoir for malaria parasites. Any attempt at malaria eradication therefore must target a wider population and should not only focus on children or individuals with a positive RDT. In endemic regions, surveys should be conducted on a regular basis.The present study conducted in the rainy season in the forest zone of Ghana reveals a very high prevalence of asymptomatic Plasmodium infections in adult residents of rural areas in the Ashanti region. A study conducted in 1998 observed a prevalence detected by microscopy of 51% in the forest area of the Ashanti region with a peak among 8-year-old children and a plateau at about 20% in adults [This is the first study on molecular prevalence of asymptomatic n adults . The preP. falciparum carriage rates detected by PCR among all age-groups were 14% during the dry season [P. falciparum infection was 72% in asymptomatic adults > 19 years recruited in the rainy season in 2000 [P. falciparum infection assessed by combined microscopy and PCR was 64% and 27% in the wet and dry seasons, respectively [In a study including 160 asymptomatic adults and children from the Greater Accra Region in Southern Ghana, the prevalence of asymptomatic parasite carriers based on microscopy was 34% and 4% in a high and low malaria transmission area, respectively . However in 2000 . Among aectively .P. falciparum parasitaemia observed in the present study was, therefore, similar to studies conducted in the rainy season in the Guinea Savannah zone [With 68%, the prevalence of asymptomatic nah zone , 18 and nah zone . In a crnah zone . DespiteP. ovale have not been widely reported specifically in asymptomatic Ghanaian adults before. Plasmodium ovale was identified in nearly 10% of the study participants, with similar numbers of individuals positive for P. o. curtisi and P. o. wallikeri. The importance of the identification of P. ovale is increasingly recognized, since both subtypes are perceived as relapsing malarial parasites, with P. o. curtisi reappearing in shorter time intervals compared to P. o. wallikeri [P. malariae were also common with 8% in the present study. Comparable to the study from Gabon [P. falciparum.Subtypes of allikeri . Asymptoom Gabon , non-falPlasmodium species carriers were detected by RDT. Even if very faint bands were interpreted as positive, the sensitivity of the RDT was still less than 50%. In a study on MSAT in Zanzibar, anti-malarial treatment of RDT-positive individuals did not reduce subsequent malaria incidence, compared with control areas. Only 4% of parasite carriers were detected by RDT compared to PCR in that study [Even though the WHO suggests that even faint RDT bands should be interpreted as positive, a recent study concluded that it is possible to interpret faint test bands as malaria negative if the patient does not have risk factors of developing severe malaria . In the at study . In the at study .The considerable variance in the sensitivity of RDTs among different studies highlights that molecular diagnostic tools are necessary to adequately assess the malaria prevalence and improve MSAT programmes.Asymptomatic parasitaemia in adults, including cases with non-falciparum species, constitutes a relevant reservoir for transmission in the Ghanaian forest zone and must be considered in efforts towards elimination of malaria.