Sixty years trying to define the malaria burden in Africa: have we made any progress?

Severe outcomes of malaria in children under time-varying exposure

In malaria epidemiology, interpolation frameworks based on available observations are critical for policy decisions and interpreting disease burden. Updating our understanding of the empirical evidence across different populations, settings, and timeframes is crucial to improving inference for supporting public health. Here, via individual-based modeling, we evaluate a large, multicountry, contemporary Plasmodium falciparum severe malaria dataset to better understand the relationship between prevalence and incidence of malaria pediatric hospitalizations - a proxy of malaria severe outcomes- in East-Africa. We find that life-long exposure dynamics, and subsequent protection patterns in children, substantially determine the likelihood of malaria hospitalizations relative to ongoing prevalence at the population level. Unsteady transmission patterns over a lifetime in children -increasing or decreasing- lead to an exponential relationship of hospitalization rates versus prevalence rather than the asymptotic pattern observed under steady transmission. Addressing this increase in the complexity of malaria epidemiology is crucial to update burden assessments via inference models that guide current and future policy decisions.

One hundred malaria attacks since birth. A longitudinal study of African children and young adults exposed to high malaria transmission

Background

Despite significant progress in malaria control over the past twenty years, malaria remains a leading cause of child morbidity and mortality in Tropical Africa. As most patients do not consult any health facility much uncertainty persists about the true burden of the disease and the range of individual differences in susceptibility to malaria.

Methods

Over a 25-years period, from 1990 to 2015, the inhabitants of Dielmo village, Senegal, an area of intense malaria transmission, have been monitored daily for their presence in the village and the occurrence of diseases. In case of fever thick blood films were systematically examined through microscopy for malaria parasites and patients received prompt diagnosis and treatment.

Findings

We analysed data collected in 111 children and young adults monitored for at least 10 years (mean 17.3 years, maximum 25 years) enrolled either at birth (95 persons) or during the two first years of life. A total of 11,599 episodes of fever were documented, including 5268 malaria attacks. The maximum number of malaria attacks in a single person was 112. Three other persons suffered one hundred or more malaria attacks during follow-up. The minimum number of malaria attacks in a single person was 11. The mean numbers of malaria attacks in children reaching their 4th, 7th, and 10th birthdays were 23.0, 37.7, and 43.6 attacks since birth, respectively. Sixteen children (14.4%) suffered ten or more malaria attacks each year at ages 1-3 years, and six children (5.4%) each year at age 4-6 years.

Interpretation

Long-term close monitoring shows that in highly endemic areas the malaria burden is higher than expected. Susceptibility to the disease may vary up to 10-fold, and for most children childhood is an endless history of malaria fever episodes. No other parasitic, bacterial or viral infection in human populations has such an impact on health.

Funding

The Pasteur Institutes of Dakar and Paris, the Institut de Recherche pour le Développement, and the French Ministry of Cooperation provided funding.

Knowledge, attitude and practices of malaria preventive measures among mothers with children under five years in a rural setting of Ghana

BACKGROUND

Malaria remains a major public health concern around the world, particularly in resource-constrained countries. Malaria still accounts for 40% of all Out-Patient Department (OPD) cases in Ghana, with children under the age of five being the most vulnerable group. The study assessed the knowledge, attitudes, and practices of malaria preventive measures among mothers with children under 5 years old in a rural setting in Ghana.

METHODS

A cross-sectional study design with a quantitative approach was used in this study. The study was facility based and involved the use of interviewer administered questionnaires to collect data from 281 mothers with children under the age of five. Simple random sampling method was used to select the respondents. The data collected was analysed using the statistical package for the social sciences (SPSS) version 22 and results presented in tables.

RESULTS

There were 281 mothers, with 59.4% having children at the age of a year. The findings revealed that the majority of participants have a high level of knowledge about malaria's causes, signs, and symptoms. Again, the majority of participants demonstrated a positive attitude toward malaria prevention, such as seeking treatment at a hospital within 24 h of suspecting their children had malaria and demonstrating good knowledge of malaria prevention practices. Despite this, 35.5% of respondents were not actively engaged in malaria prevention practices in a day prior to the interview. Respondents' occupation, level of education, and religion had a statistically significant association with mothers' attitude towards prevention (p-values < 0.05 and 0.01).

CONCLUSION

The study's findings clearly demonstrate that the majority of mothers were knowledgeable about the causes, signs and symptoms, and preventive measures of malaria in children under the age of five. There was also statistically significant association between mothers' demographic information, including level of education, occupation, religion, and their attitude towards malaria prevention. A keen interest should be directed toward the consistent application of low-cost preventive measures.

Malaria profile and socioeconomic predictors among under-five children: an analysis of 11 sub-Saharan African countries

BACKGROUND

African region accounts for 95% of all malaria cases and 96% of malaria deaths with under-five children accounting for 80% of all deaths in the region. This study assessed the socioeconomic determinants of malaria prevalence and provide evidence on the socioeconomic profile of malaria infection among under-five children in 11 SSA countries.

METHODS

This study used data from the 2010 to 2020 Demographic and Health Survey (DHS). The survey used a two-stage stratified-cluster sampling design based on the sampling frame of the population and housing census of countries included. Statistical analyses relied on Pearson's χ2, using the CHAID decision-tree algorithm and logistic regression implemented in R V.4.6.

RESULTS

Of 8547 children considered, 24.2% (95% confidence interval CI 23.4-25.05%) had malaria infection. Also, the prevalence of malaria infection seems to increase with age. The following variables are statistically associated with the prevalence of malaria infection among under-five children: under-five child's age, maternal education, sex of household head, household wealth index, place of residence, and African region where mother-child pair lives. Children whose mothers have secondary education have about 56% lower risk (odds ratio = 0.44; 95% CI 0.40-0.48) of malaria infection and 73% lower (odds ratio = 0.37; 95% CI 0.32-0.43) among children living in the richest households, compared to children living in the poorest households.

CONCLUSIONS

The findings of this study provide unique insights on how socioeconomic and demographic variables, especially maternal education level significantly predicts under-five malaria prevalence across the SSA region. Therefore, ensuring that malaria interventions are underpinned by a multisectoral approach that comprehensively tackles the interplay of maternal education and other socioeconomic variables will be critical in attaining malaria prevention and control targets in SSA.

It Is Time to Strengthen the Malaria Control Policy of the Democratic Republic of Congo and Include Schools and School-Age Children in Malaria Control Measures

Despite a decade of sustained malaria control, malaria remains a serious public health problem in the Democratic Republic of Congo (DRC). Children under five years of age and school-age children aged 5–15 years remain at high risk of symptomatic and asymptomatic malaria infections. The World Health Organization’s malaria control, elimination, and eradication recommendations are still only partially implemented in DRC. For better malaria control and eventual elimination, the integration of all individuals into the national malaria control programme will strengthen malaria control and elimination strategies in the country. Thus, inclusion of schools and school-age children in DRC malaria control interventions is needed.

Factors influencing severity of recurrent malaria in a conflict-affected state of South Sudan: an unmatched case-control study

Background

The burden of malaria remains the highest in sub-Saharan Africa and South Sudan is not an exception. The country has borne the brunt of years of chronic warfare and remains endemic of malaria, with increasing mortality and morbidity. Limited data still exists on factors influencing the recurrence of severe malaria, especially in emergency contexts such as South Sudan, affected by various conflicts and humanitarian situations. This study therefore aimed to investigate factors influencing severity of occurrence malaria in selected primary healthcare centres in South Sudan. This would assist and guide in malaria prevention, treatment, and eradication efforts.

Methods

We conducted an unmatched case-control study using routinely collected clinic data for individuals aged 1 year and above who received a diagnosis of severe malaria at 3 primary healthcare centres (PHCC); Malual Bab PHCC, Matangai PHCC and Malek PHCC between September 15, 2019 to December 15, 2019 in South Sudan. Patient characteristics were analyzed using simple descriptive statistics. Inferential statistics were also conducted to identify the associated factors influencing recurrence of severe malaria. All analyses were conducted using R Version 3.6.2.

Results

A total of 289 recurrent malaria cases were included in this study. More than half of the participants were female. Overall, the prevalence of severe recurrent malaria was 66.1% (191) while 74.4% (215) did not complete malaria treatment. Among those who did not complete malaria treatment, 76.7% (165) had severe recurrent malaria, while among those who completed malaria treatment 35.1% (26) had severe recurrent malaria (p < 0.001). There is a significant association between marital status (OR 0.33, 95% CI 0.19–0.56, p < 0.001), employment status (OR 0.35, 95% CI 0.14–0.87, p = 0.024), the use of preventive measures (OR 3.82, 95% CI 1.81–8.43, p < 0.001) and nutrition status (OR 0.22, 95% CI 0.13–0.37, p < 0.001). When adjusted for employment, marital status, nutritional and prevention measures in turns using Mantel–Haenszel test of association, this effect remained statistically significant.

Conclusions

Our study showed that there is a high prevalence of severe recurrent malaria in South Sudan and that a significant relationship exists between severe recurrent malaria and antimalarial treatment dosage completion influenced by certain personal and social factors such as marital status, employment status, the use of preventive measures and nutrition status. Findings from our study would be useful for effective response to control and prevent malaria in endemic areas of South Sudan.

Malaria hospitalisation in East Africa: age, phenotype and transmission intensity

BACKGROUND

Understanding the age patterns of disease is necessary to target interventions to maximise cost-effective impact. New malaria chemoprevention and vaccine initiatives target young children attending routine immunisation services. Here we explore the relationships between age and severity of malaria hospitalisation versus malaria transmission intensity.

METHODS

Clinical data from 21 surveillance hospitals in East Africa were reviewed. Malaria admissions aged 1 month to 14 years from discrete administrative areas since 2006 were identified. Each site-time period was matched to a model estimated community-based age-corrected parasite prevalence to provide predictions of prevalence in childhood (PfPR2-10). Admission with all-cause malaria, severe malaria anaemia (SMA), respiratory distress (RD) and cerebral malaria (CM) were analysed as means and predicted probabilities from Bayesian generalised mixed models.

RESULTS

52,684 malaria admissions aged 1 month to 14 years were described at 21 hospitals from 49 site-time locations where PfPR2-10 varied from < 1 to 48.7%. Twelve site-time periods were described as low transmission (PfPR2-10 < 5%), five low-moderate transmission (PfPR2-10 5-9%), 20 moderate transmission (PfPR2-10 10-29%) and 12 high transmission (PfPR2-10 ≥ 30%). The majority of malaria admissions were below 5 years of age (69-85%) and rare among children aged 10-14 years (0.7-5.4%) across all transmission settings. The mean age of all-cause malaria hospitalisation was 49.5 months (95% CI 45.1, 55.4) under low transmission compared with 34.1 months (95% CI 30.4, 38.3) at high transmission, with similar trends for each severe malaria phenotype. CM presented among older children at a mean of 48.7 months compared with 39.0 months and 33.7 months for SMA and RD, respectively. In moderate and high transmission settings, 34% and 42% of the children were aged between 2 and 23 months and so within the age range targeted by chemoprevention or vaccines.

CONCLUSIONS

Targeting chemoprevention or vaccination programmes to areas where community-based parasite prevalence is ≥10% is likely to match the age ranges covered by interventions (e.g. intermittent presumptive treatment in infancy to children aged 2-23 months and current vaccine age eligibility and duration of efficacy) and the age ranges of highest disease burden.

Population modification strategies for malaria vector control are uniquely resilient to observed levels of gene drive resistance alleles

Cas9/guide RNA (gRNA)-based gene drive systems are expected to play a transformative role in malaria elimination efforts., whether through population modification, in which the drive system contains parasite-refractory genes, or population suppression, in which the drive system induces a severe fitness load resulting in population decline or extinction. DNA sequence polymorphisms representing alternate alleles at gRNA target sites may confer a drive-resistant phenotype in individuals carrying them. Modeling predicts that, for observed levels of SGV at potential target sites and observed rates of de novo DRA formation, population modification strategies are uniquely resilient to DRAs. We conclude that gene drives can succeed when fitness costs incurred by drive-carrying mosquitoes are low enough to prevent strong positive selection for DRAs produced de novo or as part of the SGV and that population modification strategies are less prone to failure due to drive resistance.

Are Vulnerable Communities Thoroughly Informed on Mosquito Bio-Ecology and Burden?

Mosquitoes account for a significant burden of morbidity and mortality globally. Despite evidence of (1) imminent anthropogenic climate and environmental changes, (2) vector-pathogen spatio-temporal dynamics and (3) emerging and re-emerging mosquito borne infections, public knowledge on mosquito bio-ecology remain scant. In particular, knowledge, attitude and practices (KAPs) on mosquitoes are often neglected despite otherwise expensive remedial efforts against consequent infections and other indirect effects associated with disease burden. To gather baseline KAPs that identify gaps for optimising vector-borne disease control, we surveyed communities across endemic and non-endemic malaria sub-districts (Botswana). The study revealed limited knowledge of mosquitoes and their infections uniformly across endemic and non-endemic areas. In addition, a significant proportion of respondents were concerned about mosquito burdens, although their level of personal, indoor and environmental protection practices varied significantly across sub-districts. Given the limited knowledge displayed by the communities, this study facilitates bridging KAP gaps to minimise disease burdens by strengthening public education. Furthermore, it provides a baseline for future studies in mosquito bio-ecology and desirable control practices across differential spheres of the rural–urban lifestyle, with implications for enhanced livelihoods as a consequence of improved public health.

Malaria infection, disease and mortality among children and adults on the coast of Kenya

BACKGROUND

Malaria transmission has recently fallen in many parts of Africa, but systematic descriptions of infection and disease across all age groups are rare. Here, an epidemiological investigation of parasite prevalence, the incidence of fevers associated with infection, severe hospitalized disease and mortality among children older than 6 months and adults on the Kenyan coast is presented.

METHODS

A prospective fever surveillance was undertaken at 6 out-patients (OPD) health-facilities between March 2018 and February 2019. Four community-based, cross sectional surveys of fever history and infection prevalence were completed among randomly selected homestead members from the same communities. Paediatric and adult malaria at Kilifi county hospital was obtained for the 12 months period. Rapid Diagnostic Tests (CareStart™ RDT) to detect HRP2-specific to Plasmodium falciparum was used in the community and the OPD, and microscopy in the hospital. Crude and age-specific incidence rates were computed using Poisson regression.

RESULTS

Parasite prevalence gradually increased from childhood, reaching 12% by 9 years of age then declining through adolescence into adulthood. The incidence rate of RDT positivity in the OPD followed a similar trend to that of infection prevalence in the community. The incidence of hospitalized malaria from the same community was concentrated among children aged 6 months to 4 years (i.e. 64% and 70% of all hospitalized and severe malaria during the 12 months of surveillance, respectively). Only 3.7% (12/316) of deaths were directly attributable to malaria. Malaria mortality was highest among children aged 6 months-4 years at 0.57 per 1000 person-years (95% CI 0.2, 1.2). Severe malaria and death from malaria was negligible above 15 years of age.

CONCLUSION

Under conditions of low transmission intensity, immunity to disease and the fatal consequences of infection appear to continue to be acquired in childhood and faster than anti-parasitic immunity. There was no evidence of an emerging significant burden of severe malaria or malaria mortality among adults. This is contrary to current modelled approaches to disease burden estimation in Africa and has important implications for the targeting of infection prevention strategies based on chemoprevention or vector control.

Routine data for malaria morbidity estimation in Africa: challenges and prospects

BACKGROUND

The burden of malaria in sub-Saharan Africa remains challenging to measure relying on epidemiological modelling to evaluate the impact of investments and providing an in-depth analysis of progress and trends in malaria response globally. In malaria-endemic countries of Africa, there is increasing use of routine surveillance data to define national strategic targets, estimate malaria case burdens and measure control progress to identify financing priorities. Existing research focuses mainly on the strengths of these data with less emphasis on existing challenges and opportunities presented.

CONCLUSION

Here we define the current imperfections common to routine malaria morbidity data at national levels and offer prospects into their future use to reflect changing disease burdens.

Sub-national stratification of malaria risk in mainland Tanzania: a simplified assembly of survey and routine data

BACKGROUND

Recent malaria control efforts in mainland Tanzania have led to progressive changes in the prevalence of malaria infection in children, from 18.1% (2008) to 7.3% (2017). As the landscape of malaria transmission changes, a sub-national stratification becomes crucial for optimized cost-effective implementation of interventions. This paper describes the processes, data and outputs of the approach used to produce a simplified, pragmatic malaria risk stratification of 184 councils in mainland Tanzania.

METHODS

Assemblies of annual parasite incidence and fever test positivity rate for the period 2016-2017 as well as confirmed malaria incidence and malaria positivity in pregnant women for the period 2015-2017 were obtained from routine district health information software. In addition, parasite prevalence in school children (PfPR5to16) were obtained from the two latest biennial council representative school malaria parasitaemia surveys, 2014-2015 and 2017. The PfPR5to16 served as a guide to set appropriate cut-offs for the other indicators. For each indicator, the maximum value from the past 3 years was used to allocate councils to one of four risk groups: very low (< 1%PfPR5to16), low (1- < 5%PfPR5to16), moderate (5- < 30%PfPR5to16) and high (≥ 30%PfPR5to16). Scores were assigned to each risk group per indicator per council and the total score was used to determine the overall risk strata of all councils.

RESULTS

Out of 184 councils, 28 were in the very low stratum (12% of the population), 34 in the low stratum (28% of population), 49 in the moderate stratum (23% of population) and 73 in the high stratum (37% of population). Geographically, most of the councils in the low and very low strata were situated in the central corridor running from the north-east to south-west parts of the country, whilst the areas in the moderate to high strata were situated in the north-west and south-east regions.

CONCLUSION

A stratification approach based on multiple routine and survey malaria information was developed. This pragmatic approach can be rapidly reproduced without the use of sophisticated statistical methods, hence, lies within the scope of national malaria programmes across Africa.

A systematic review of changing malaria disease burden in sub-Saharan Africa since 2000: comparing model predictions and empirical observations

BACKGROUND

The most widely used measures of declining burden of malaria across sub-Saharan Africa are predictions from geospatial models. These models apply spatiotemporal autocorrelations and covariates to parasite prevalence data and then use a function of parasite prevalence to predict clinical malaria incidence. We attempted to assess whether trends in malaria cases, based on local surveillance, were similar to those captured by Malaria Atlas Project (MAP) incidence surfaces.

METHODS

We undertook a systematic review (PROSPERO International Prospective Register of Systematic Reviews; ID = CRD42019116834) to identify empirical data on clinical malaria in Africa since 2000, where reports covered at least 5 continuous years. The trends in empirical data were then compared with the trends of time-space matched clinical malaria incidence from MAP using the Spearman rank correlation. The correlations (rho) between changes in empirically observed and modelled estimates of clinical malaria were displayed by forest plots and examined by meta-regression.

RESULTS

Sixty-seven articles met our inclusion criteria representing 124 sites from 24 African countries. The single most important factor explaining the correlation between empirical observations and modelled predictions was the slope of empirically observed data over time (rho = - 0.989; 95% CI - 0.998, - 0.939; p < 0.001), i.e. steeper declines were associated with a stronger correlation between empirical observations and modelled predictions. Factors such as quality of study, reported measure of malaria and endemicity were only slightly predictive of such correlations.

CONCLUSIONS

In many locations, both local surveillance data and modelled estimates showed declines in malaria burden and hence similar trends. However, there was a weak association between individual surveillance datasets and the modelled predictions where stalling in progress or resurgence of malaria burden was empirically observed. Surveillance data were patchy, indicating a need for improved surveillance to strengthen both empiric reporting and modelled predictions.

Modelling the relationship between malaria prevalence as a measure of transmission and mortality across age groups

Background

Parasite prevalence has been used widely as a measure of malaria transmission, especially in malaria endemic areas. However, its contribution and relationship to malaria mortality across different age groups has not been well investigated. Previous studies in a health and demographic surveillance systems (HDSS) platform in western Kenya quantified the contribution of incidence and entomological inoculation rates (EIR) to mortality. The study assessed the relationship between outcomes of malaria parasitaemia surveys and mortality across age groups.

Methods

Parasitological data from annual cross-sectional surveys from the Kisumu HDSS between 2007 and 2015 were used to determine malaria parasite prevalence (PP) and clinical malaria (parasites plus reported fever within 24 h or temperature above 37.5 °C). Household surveys and verbal autopsy (VA) were used to obtain data on all-cause and malaria-specific mortality. Bayesian negative binomial geo-statistical regression models were used to investigate the association of PP/clinical malaria with mortality across different age groups. Estimates based on yearly data were compared with those from aggregated data over 4 to 5-year periods, which is the typical period that mortality data are available from national demographic and health surveys.

Results

Using 5-year aggregated data, associations were established between parasite prevalence and malaria-specific mortality in the whole population (RR_malaria = 1.66; 95% Bayesian Credible Intervals: 1.07–2.54) and children 1–4 years (RR_malaria = 2.29; 1.17–4.29). While clinical malaria was associated with both all-cause and malaria-specific mortality in combined ages (RR_all-cause = 1.32; 1.01–1.74); (RR_malaria = 2.50; 1.27–4.81), children 1–4 years (RR_all-cause = 1.89; 1.00–3.51); (RR_malaria = 3.37; 1.23–8.93) and in older children 5–14 years (RR_all-cause = 3.94; 1.34–11.10); (RR_malaria = 7.56; 1.20–39.54), no association was found among neonates, adults (15–59 years) and the elderly (60+ years). Distance to health facilities, socioeconomic status, elevation and survey year were important factors for all-cause and malaria-specific mortality.

Conclusion

Malaria parasitaemia from cross-sectional surveys was associated with mortality across age groups over 4 to 5 year periods with clinical malaria more strongly associated with mortality than parasite prevalence. This effect was stronger in children 5–14 years compared to other age-groups. Further analyses of data from other HDSS sites or similar platforms would be useful in investigating the relationship between malaria and mortality across different endemicity levels.

Electronic supplementary material

The online version of this article (10.1186/s12936-019-2869-9) contains supplementary material, which is available to authorized users.

The indirect health effects of malaria estimated from health advantages of the sickle cell trait

Most estimates of the burden of malaria are based on its direct impacts; however, its true burden is likely to be greater because of its wider effects on overall health. Here we estimate the indirect impact of malaria on children's health in a case-control study, using the sickle cell trait (HbAS), a condition associated with a high degree of specific malaria resistance, as a proxy indicator for an effective intervention. We estimate the odds ratios for HbAS among cases (all children admitted to Kilifi County Hospital during 2000-2004) versus community controls. As expected, HbAS protects strongly against malaria admissions (aOR 0.26; 95%CI 0.22-0.31), but it also protects against other syndromes, including neonatal conditions (aOR 0.79; 0.67-0.93), bacteraemia (aOR 0.69; 0.54-0.88) and severe malnutrition (aOR 0.67; 0.55-0.83). The wider health impacts of malaria should be considered when estimating the potential added benefits of effective malaria interventions.

School-based malaria prevalence: informative systematic surveillance measure to assess epidemiological impact of malaria control interventions in the Democratic Republic of the Congo

Background

In southern Democratic Republic of the Congo, malaria transmission is stable with seasonal fluctuations. Different measurements can be used to monitor disease burden and estimate the performance of control programmes. Repeated school-based malaria prevalence surveys (SMPS) were conducted from 2007 to 2014 to generate up-to-date surveillance data and evaluate the impact of an integrated vector control programme.

Methods

Biannual SMPS used a stratified, randomized and proportional sampling method. Schools were randomly selected from the entire pool of facilities within each Health Area (HA). Subsequently, school-children from 6 to 12 years of age were randomly selected in a proportional manner. Initial point-of-care malaria diagnosis was made using a rapid detection test. A matching stained blood film was later examined by expert microscopy and used in the final analysis. Data was stratified and analysed based on age, survey time and location.

Results

The baseline SMPS (pre-control in 2007) prevalence was approximately 77%. From 2009 to 2014, 11,628 school-children were randomly screened. The mean age was 8.7 years with a near equal sex ratio. After exclusion, analysis of 10,493 students showed an overall malaria prevalence ratio of 1.92 in rural compared to urbanized areas. The distribution of Plasmodium falciparum malaria was significantly different between rural and urban HAs and between end of wet season and end of dry season surveys. The combined prevalence of single P. falciparum, Plasmodium malariae and Plasmodium ovale infections were 29.9, 1.8 and 0.3% of those examined, respectively. Only 1.8% were mixed Plasmodium species infections. From all microscopically detected infections (3545 of 10,493 samples examined), P. falciparum represented 88.5%, followed by P. malariae (5.4%) and P. ovale (0.8%). Cases with multiple species represented 5.3% of patent infections. Malaria prevalence was independent of age and gender. Control programme performance contributed to a significant decrease in mean P. falciparum infection density in urban compared to rural locations. Some rural areas remained highly refractory to control measures (insecticide-treated bed nets, periodic indoor residual spraying).

Conclusion

The SMPS is a useful longitudinal measurement for estimating population malaria prevalence and demonstrating disease burden and impact of control interventions. SMPS can identify refractory areas of transmission and thus prioritize control strategies accordingly.

Hospital Mortality - a neglected but rich source of information supporting the transition to higher quality health systems in low and middle income countries

BACKGROUND

There is increasing focus on the strength of primary health care systems in low and middle-income countries (LMIC). There are important roles for higher quality district hospital care within these systems. These hospitals are also sources of information of considerable importance to health systems, but this role, as with the wider roles of district hospitals, has been neglected.

KEY MESSAGES

As we make efforts to develop higher quality health systems in LMIC we highlight the critical importance of district hospitals focusing here on how data on hospital mortality offers value: i) in understanding disease burden; ii) as part of surveillance and impact monitoring; iii) as an entry point to exploring system failures; and iv) as a lens to examine variability in health system performance and possibly as a measure of health system quality in its own right. However, attention needs paying to improving data quality by addressing reporting gaps and cause of death reporting. Ideally enabling the collection of basic, standardised patient level data might support at least simple case-mix and case-severity adjustment helping us understand variation. Better mortality data could support impact evaluation, benchmarking, exploration of links between health system inputs and outcomes and critical scrutiny of geographic variation in quality and outcomes of care. Improved hospital information is a neglected but broadly valuable public good.

CONCLUSION

Accurate, complete and timely hospital mortality reporting is a key attribute of a functioning health system. It can support countries' efforts to transition to higher quality health systems in LMIC enabling national and local advocacy, accountability and action.

True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries

BACKGROUND

Malaria is one of the major causes of childhood death in sub-Saharan countries. A reliable estimation of malaria prevalence is important to guide and monitor progress toward control and elimination. The aim of the study was to estimate the true prevalence of malaria in children under five in the Democratic Republic of the Congo, Uganda and Kenya, using a Bayesian modelling framework that combined in a novel way malaria data from national household surveys with external information about the sensitivity and specificity of the malaria diagnostic methods used in those surveys-i.e., rapid diagnostic tests and light microscopy.

METHODS

Data were used from the Demographic and Health Surveys (DHS) and Malaria Indicator Surveys (MIS) conducted in the Democratic Republic of the Congo (DHS 2013-2014), Uganda (MIS 2014-2015) and Kenya (MIS 2015), where information on infection status using rapid diagnostic tests and/or light microscopy was available for 13,573 children. True prevalence was estimated using a Bayesian model that accounted for the conditional dependence between the two diagnostic methods, and the uncertainty of their sensitivities and specificities obtained from expert opinion.

RESULTS

The estimated true malaria prevalence was 20% (95% uncertainty interval [UI] 17%-23%) in the Democratic Republic of the Congo, 22% (95% UI 9-32%) in Uganda and 1% (95% UI 0-3%) in Kenya. According to the model estimations, rapid diagnostic tests had a satisfactory sensitivity and specificity, and light microscopy had a variable sensitivity, but a satisfactory specificity. Adding reported history of fever in the previous 14 days as a third diagnostic method to the model did not affect model estimates, highlighting the poor performance of this indicator as a malaria diagnostic.

CONCLUSIONS

In the absence of a gold standard test, Bayesian models can assist in the optimal estimation of the malaria burden, using individual results from several tests and expert opinion about the performance of those tests.

Plasmodium falciparum

Plasmodium falciparum is a protozoan parasite that causes the most severe form of human malaria. Five other Plasmodium species can also infect humans - P. vivax, P. malariae, P. ovale curtisi, P. ovale wallikeri and P. knowlesi - but P. falciparum is the most prevalent Plasmodium species in the African region, where 90% of all malaria occurs, and it is this species that causes the great majority of malaria deaths. These were reported by the WHO at 438 000 in 2015 from an estimated 214 million cases; importantly, however, figures for the global burden of malaria tend to have wide margins of error due to poor and inaccurate reporting. In this Perspective, features of P. falciparum that are unique among human malaria parasites are highlighted, and current issues surrounding the control and treatment of this major human pathogen are discussed.

Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys

Background

One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was conducted.

Methods

Using malaria indicators, data were assembled in nine sub-Saharan African countries with at least two nationally-representative surveys. A Bayesian statistical model was used to estimate between- and within-cluster variability for fever and malaria prevalence, and insecticide-treated bed nets (ITNs) use in children under the age of 5 years. The intra-class correlation coefficient was estimated along with the optimal sample size for each indicator with associated uncertainty.

Findings

Results suggest that the estimated sample sizes for the current nationally-representative surveys increases with declining malaria prevalence. Comparison between the actual sample size and the modelled estimate showed a requirement to increase the sample size for parasite prevalence by up to 77.7% (95% Bayesian credible intervals 74.7–79.4) for the 2015 Kenya MIS (estimated sample size of children 0–4 years 7218 [7099–7288]), and 54.1% [50.1–56.5] for the 2014–2015 Rwanda DHS (12,220 [11,950–12,410]).

Conclusion

This study highlights the importance of defining indicator-relevant sample sizes to achieve the required precision in the current national surveys. While expanding the current surveys would need additional investment, the study highlights the need for improved approaches to cost effective sampling.

Electronic supplementary material

The online version of this article (10.1186/s12936-017-2127-y) contains supplementary material, which is available to authorized users.

A systematic review and synthesis of the strengths and limitations of measuring malaria mortality through verbal autopsy

Background

Lack of valid and reliable data on malaria deaths continues to be a problem that plagues the global health community. To address this gap, the verbal autopsy (VA) method was developed to ascertain cause of death at the population level. Despite the adoption and wide use of VA, there are many recognized limitations of VA tools and methods, especially for measuring malaria mortality. This study synthesizes the strengths and limitations of existing VA tools and methods for measuring malaria mortality (MM) in low- and middle-income countries through a systematic literature review.

Methods

The authors searched PubMed, Cochrane Library, Popline, WHOLIS, Google Scholar, and INDEPTH Network Health and Demographic Surveillance System sites’ websites from 1 January 1990 to 15 January 2016 for articles and reports on MM measurement through VA. Inclusion criteria: article presented results from a VA study where malaria was a cause of death; article discussed limitations/challenges related to measurement of MM through VA. Two authors independently searched the databases and websites and conducted a synthesis of articles using a standard matrix.

Results

The authors identified 828 publications; 88 were included in the final review. Most publications were VA studies; others were systematic reviews discussing VA tools or methods; editorials or commentaries; and studies using VA data to develop MM estimates. The main limitation were low sensitivity and specificity of VA tools for measuring MM. Other limitations included lack of standardized VA tools and methods, lack of a ‘true’ gold standard to assess accuracy of VA malaria mortality.

Conclusions

Existing VA tools and methods for measuring MM have limitations. Given the need for data to measure progress toward the World Health Organization’s Global Technical Strategy for Malaria 2016–2030 goals, the malaria community should define strategies for improving MM estimates, including exploring whether VA tools and methods could be further improved. Longer term strategies should focus on improving countries’ vital registration systems for more robust and timely cause of death data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-017-2071-x) contains supplementary material, which is available to authorized users.

Plasmodium falciparum var genes expressed in children with severe malaria encode CIDRα1 domains

Most severe Plasmodium falciparum infections are experienced by young children. Severe symptoms are precipitated by vascular sequestration of parasites expressing a particular subset of the polymorphic P. falciparum erythrocyte membrane protein 1 (PfEMP1) adhesion molecules. Parasites binding human endothelial protein C receptor (EPCR) through the CIDRα1 domain of certain PfEMP1 were recently associated with severe malaria in children. However, it has remained unclear to which extend the EPCR‐binding CIDRα1 domains epitomize PfEMP1 expressed in severe malaria. Here, we characterized the near full‐length transcripts dominating the var transcriptome in children with severe malaria and found that the only common feature of the encoded PfEMP1 was CIDRα1 domains. Such genes were highly and dominantly expressed in both children with severe malarial anaemia and cerebral malaria. These observations support the hypothesis that the CIDRα1‐EPCR interaction is key to the pathogenesis of severe malaria and strengthen the rationale for pursuing a vaccine or adjunctive treatment aiming at inhibiting or reducing the damaging effects of this interaction.

Advances in mapping malaria for elimination: fine resolution modelling of Plasmodium falciparum incidence

The long-term goal of the global effort to tackle malaria is national and regional elimination and eventually eradication. Fine scale multi-temporal mapping in low malaria transmission settings remains a challenge and the World Health Organisation propose use of surveillance in elimination settings. Here, we show how malaria incidence can be modelled at a fine spatial and temporal resolution from health facility data to help focus surveillance and control to population not attending health facilities. Using Namibia as a case study, we predicted the incidence of malaria, via a Bayesian spatio-temporal model, at a fine spatial resolution from parasitologically confirmed malaria cases and incorporated metrics on healthcare use as well as measures of uncertainty associated with incidence predictions. We then combined the incidence estimates with population maps to estimate clinical burdens and show the benefits of such mapping to identifying areas and seasons that can be targeted for improved surveillance and interventions. Fine spatial resolution maps produced using this approach were then used to target resources to specific local populations, and to specific months of the season. This remote targeting can be especially effective where the population distribution is sparse and further surveillance can be limited to specific local areas.

Treatment-seeking rates in malaria endemic countries

Background

The proportion of individuals who seek treatment for fever is an important quantity in understanding access to and use of health systems, as well as for interpreting data on disease incidence from routine surveillance systems. For many malaria endemic countries (MECs), treatment-seeking information is available from national household surveys. The aim of this paper was to assemble sub-national estimates of treatment-seeking behaviours and to predict national treatment-seeking measures for all MECs lacking household survey data.

Methods

Data on treatment seeking for fever were obtained from Demographic and Health Surveys, Malaria Indicator Surveys and Multiple Cluster Indicator Surveys for every MEC and year that data were available. National-level social, economic and health-related variables were gathered from the World Bank as putative covariates of treatment-seeking rates. A generalized additive mixed model (GAMM) was used to estimate treatment-seeking behaviours for countries where survey data were unavailable. Two separate models were developed to predict the proportion of fever cases that would seek treatment at (1) a public health facility or (2) from any kind of treatment provider.

Results

Treatment-seeking data were available for 74 MECs and modelled for the remaining 24. GAMMs found that the percentage of pregnant women receiving prenatal care, vaccination rates, education level, government health expenditure, and GDP growth were important predictors for both categories of treatment-seeking outcomes. Treatment-seeking rates, which varied both within and among regions, revealed that public facilities were not always the primary facility type used.

Conclusions

Estimates of treatment-seeking rates show how health services are utilized and help correct reported malaria case numbers to obtain more accurate measures of disease burden. The assembled and modelled data demonstrated that while treatment-seeking rates have overall increased over time, access remains low in some malaria endemic regions and utilization of government services is in some areas limited.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-015-1048-x) contains supplementary material, which is available to authorized users.

Comparing insecticide-treated bed net use to Plasmodium falciparum infection among schoolchildren living near Lake Victoria, Kenya

Background

Under trial conditions insecticide-treated nets have been shown to provide significant clinical and mortality protection under a range of malaria transmission intensity conditions. There are, however, few operational impact data, notably in very intense transmission conditions. This study, reports on malaria infection among Kenyan schoolchildren living in areas of intense malaria transmission and their reported use of insecticide-treated bed nets.

Methods

5188 children in 54 schools were randomly sampled from seven counties surrounding Lake Victoria between May and June 2014. A questionnaire was administered to schoolchildren in classes 2–6 on the use of a long-lasting, insecticide-treated net (LLIN) the night before the survey and provided a single blood sample for a rapid diagnostic test for malaria infection. Analysis of the impact of insecticide-treated net use on malaria prevalence was undertaken using a multivariable, mixed effects, logistic regression at 95 % confidence interval (CI), taking into account hierarchical nature of the data and results adjusted for school clusters.

Results

The overall prevalence of malaria infection was 48.7 %, two-thirds (67.9 %) of the children reported using LLIN, 91.3 % of the children reported that their households own at least one LLIN and the household LLIN coverage was 2.5 persons per one LLIN. The prevalence of infection showed variation across the counties, with prevalence being highest in Busia (66.9 %) and Homabay (51.8 %) counties, and lowest in Migori County (29.6 %). Generally, malaria parasite prevalence differed between age groups and gender with the highest prevalence occurring in children below 7 years (50.6 %) and males (52.2 %). Adjusting for county and school, there was a significant reduction in odds of malaria infection among the schoolchildren who reported LLIN use the previous night by 14 % (aOR 0.86, 95 % CI 0.74–0.98, P < 0.027).

Conclusion

Malaria transmission continues to be high around Lake Victoria. Despite evidence of increasing pyrethroid resistance and the likely overall efficacy of LLIN distributed several years prior to the survey, LLIN continue to provide protection against infection among school-aged children.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-015-1031-6) contains supplementary material, which is available to authorized users.

Defining the relationship between Plasmodium vivax parasite rate and clinical disease

Background

Though essential to the development and evaluation of national malaria control programmes, precise enumeration of the clinical illness burden of malaria in endemic countries remains challenging where local surveillance systems are incomplete. Strategies to infer annual incidence rates from parasite prevalence survey compilations have proven effective in the specific case of Plasmodium falciparum, but have yet to be developed for Plasmodium vivax. Moreover, defining the relationship between P. vivax prevalence and clinical incidence may also allow levels of endemicity to be inferred for areas where the information balance is reversed, that is, incident case numbers are more widely gathered than parasite surveys; both applications ultimately facilitating cartographic estimates of P. vivax transmission intensity and its ensuring disease burden.

Methods

A search for active case detection surveys was conducted and the recorded incidence values were matched to local, contemporary parasite rate measures and classified to geographic zones of differing relapse phenotypes. A hierarchical Bayesian model was fitted to these data to quantify the relationship between prevalence and incidence while accounting for variation among relapse zones.

Results

The model, fitted with 176 concurrently measured P. vivax incidence and prevalence records, was a linear regression of the logarithm of incidence against the logarithm of age-standardized prevalence. Specific relationships for the six relapse zones where data were available were drawn, as well as a pooled overall relationship. The slope of the curves varied among relapse zones; zones with short predicted time to relapse had steeper slopes than those observed to contain long-latency relapse phenotypes.

Conclusions

The fitted relationships, along with appropriate uncertainty metrics, allow for estimates of clinical incidence of known confidence to be made from wherever P. vivax prevalence data are available. This is a prerequisite for cartographic-based inferences about the global burden of morbidity due to P. vivax, which will be used to inform control efforts.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-015-0706-3) contains supplementary material, which is available to authorized users.

The past, present and future use of epidemiological intelligence to plan malaria vector control and parasite prevention in Uganda

Background

An important prelude to developing strategies to control infectious diseases is a detailed epidemiological evidence platform to target cost-effective interventions and define resource needs.

Methods

A review of published and un-published reports of malaria vector control and parasite prevention in Uganda was conducted for the period 1900–2013. The objective was to provide a perspective as to how epidemiological intelligence was used to design malaria control before and during the global malaria eradication programme (GMEP) and to contrast this with the evidence generated in support of the Roll Back Malaria (RBM) initiative from 1998 to date.

Results

During the GMEP era, comprehensive investigations were undertaken on the effectiveness of vector and parasite control such as indoor residual house-spraying (IRS) and mass drug administration (MDA) at different sites in Uganda. Nationwide malariometric surveys were undertaken between 1964 and 1967 to provide a profile of risk, epidemiology and seasonality leading to an evidence-based national cartography of risk to characterize the diversity of malaria transmission in Uganda. At the launch of the RBM initiative in the late 1990s, an equivalent level of evidence was lacking. There was no contemporary national evidence-base for the likely impact of insecticide-treated nets (ITN), no new malariometric data, no new national cartography of malaria risk or any evidence of tailored intervention delivery based on variations in the ecology of malaria risk in Uganda.

Discussion

Despite millions of dollars of overseas development assistance over the last ten years in ITN, and more recently the resurrection of the use of IRS, the epidemiological impact of vector control remains uncertain due to an absence of nationwide basic parasite and vector-based field studies.

Conclusion

Readily available epidemiological data should become the future business model to maximize malaria funding from 2015. Over the next five to ten years, accountability, impact analysis, financial business cases supported by a culture of data use should become the new paradigm by which malaria programmes, governments and their development partners operate.