Use of the slide positivity rate to estimate changes in malaria incidence in a cohort of Ugandan children

Impact of population based indoor residual spraying in combination with mass drug administration on malaria incidence and test positivity in a high transmission setting in north eastern Uganda

BACKGROUND

Mass drug administration (MDA) and indoor residual spraying (IRS) are potent malaria burden reduction tools. The impact of combining MDA and IRS is not well documented. We evaluated the impact of MDA + IRS compared to IRS alone at a high transmission site in Eastern Uganda.

METHODS

A quasi-experimental study was implemented in Toroma and Kapujan subcounties in north eastern Uganda. Both subcounties received four rounds of IRS using primiphos-methyl (Acttellic SC300) 6-8 months apart from December 2016 to December 2018. Eligible residents of Kapujan simultaneously received MDA using dihydroartemesinin-piperaquine (DHA-PQ). Health facility data was used to monitor malaria case incidence rate and test positivity rates.

RESULTS

In the MDA + IRS arm, malaria incidence dropped by 83% (IRR: 0·17 (0.16-0.18); p < 0.001) in children under 5 year and by 78% (IRR: 0·22 (0.22-0.23); p < 0.001) in persons aged ≥ 5 years from the pre-intervention to the intervention period. In the IRS arm malaria incidence dropped by 47% (IRR: 0.53 (0.51, 0.56); p < 0.001) in children under 5 years and by 71% 0.29 (0.28, 0.30); p < 0.001) in persons aged ≥ 5 years. A drastic drop occurred immediately after the intervention after which cases slowly increased in both arms. Malaria test positivity rate (TPR) dropped at a rate of 21 (p = 0.003) percentage points per 1000 persons in the MDA + IRS arm compared to the IRS arm. There was a mean decrease of 60 (p-value, 0.040) malaria cases among children under five years and a mean decrease in TPR of 16·16 (p-value, 0.001) in the MDA + IRS arm compared to IRS arm.

INTERPRETATION

MDA significantly reduced malaria burden among children < 5 years however the duration of this impact needs to be further investigated.

Assessing the utility of pregnant women as a sentinel surveillance population for malaria in Geita, Tanzania, 2019 - 2021

OBJECTIVES

Estimates of malaria burden and intervention uptake in Africa are primarily based on household surveys. However, their expense and infrequency limit their utility. We investigated whether data collected during antenatal care (ANC) can provide relevant information for decision-makers.

METHODS

Malaria test positivity rates and questionnaire data from ANC attendees at 39 health facilities were compared to questionnaire data and positivity rates among children from two cross-sectional surveys in the facilities' corresponding catchment areas.

RESULTS

Trends in parasitemia among ANC attendees were predictive of trends in parasitemia among children at the council level (mean absolute error 6.0%). Primigravid ANC attendees had the lowest rates of net ownership (modeled odds ratio [OR] 0.28, 95% CI 0.19-0.40) and use (OR 0.58, 95% CI 0.42-0.79). ANC attendees reported higher levels of care-seeking (OR 1.78, 95% CI 1.48-2.14), malaria testing (OR 4.16, 95% CI 3.44-5.04), and treatment for children with fever (OR 7.66, 95% CI 4.89-11.98) compared to women surveyed in households, raising concerns about social desirability bias disproportionately impacting ANC surveys.

CONCLUSION

ANC surveillance is an effective strategy for tracking trends in malaria burden. More work is required to elucidate the value of administering questionnaires to ANC attendees.

Spatio-temporal modelling of routine health facility data for malaria risk micro-stratification in mainland Tanzania

As malaria transmission declines, the need to monitor the heterogeneity of malaria risk at finer scales becomes critical to guide community-based targeted interventions. Although routine health facility (HF) data can provide epidemiological evidence at high spatial and temporal resolution, its incomplete nature of information can result in lower administrative units without empirical data. To overcome geographic sparsity of data and its representativeness, geo-spatial models can leverage routine information to predict risk in un-represented areas as well as estimate uncertainty of predictions. Here, a Bayesian spatio-temporal model was applied on malaria test positivity rate (TPR) data for the period 2017-2019 to predict risks at the ward level, the lowest decision-making unit in mainland Tanzania. To quantify the associated uncertainty, the probability of malaria TPR exceeding programmatic threshold was estimated. Results showed a marked spatial heterogeneity in malaria TPR across wards. 17.7 million people resided in areas where malaria TPR was high (≥ 30; 90% certainty) in the North-West and South-East parts of Tanzania. Approximately 11.7 million people lived in areas where malaria TPR was very low (< 5%; 90% certainty). HF data can be used to identify different epidemiological strata and guide malaria interventions at micro-planning units in Tanzania. These data, however, are imperfect in many settings in Africa and often require application of geo-spatial modelling techniques for estimation.

India may need an additional metric to assess the endemicity of malaria in low surveillance districts

India's National Framework for malaria elimination is essentially dependent on Annual Parasite Incidence (API). API is the primary criterion for classifying states and districts into different categories: intensified control, pre-elimination, elimination, prevention and re-establishment of malaria. However, API's validity is critically dependent on multiple factors, one such important factor is Annual Blood Examination Rate (ABER) and is often considered as indicator of operational efficiency. Therefore, the present study aimed to determine whether the API is a sufficiently good malaria index to assess malaria endemicity in India. An in-depth analysis of malaria data (2017-19) was done to determine the appropriateness of API as a sole indicator of malaria endemicity. We stratified the Indian districts into three strata based on Annual Blood Examination Rate (ABER): <5, 5.0-5.0, >15, further APIs was compared with Slide Positivity Rates (SPRs) using sign rank test, independently in each stratum. API and SPR were found comparable (p-value 0.323) in stratum 2 only. However, in the case of lower ABER (<5%, strata 1), the API was significantly lower than the SPR, and higher ABER (>15%), the API was found substantially higher than the SPR. Thus, ABER tunes the validity of API and should avoid to use as a single indicator of malaria endemicity. API is an appropriate measure of malaria endemicity in high and moderate transmission areas where surveillance is good (ABER≥5%). However, it is vitally dependent upon surveillance rate and other factors such as population size, the selection of individuals for malaria testing. Therefore, where surveillance is poor (<5%), we propose that API should be complemented with SPR and the number of cases. It will significantly aid the design and deployment of interventions in India.

Measles-Rubella Positivity Rate and Associated Factors in Pre-Mass and Post-Mass Vaccination Periods: Analysis of Uganda Routine Surveillance Laboratory Data

Toward 2019, Uganda experienced an extensive outbreak of measles and rubella. The Uganda National Expanded Programme on Immunization implemented a mass measles-rubella vaccination campaign aimed at halting the ongoing transmission. This study determined the changes in the disease burden thereafter. We conducted a retrospective cross-sectional study on measles-rubella positivity and its associated factors in Uganda using 1697 case-based surveillance data for 2019 and 2020 stratified into two dispensations: prevaccination and postvaccination campaigns. Statistical tests employed in STATA 15 included chi-square, Fisher’s exact, and binomial tests. Measles positivity rates in the period before and after the mass immunization campaign were 41.88% (95% CI: 39.30–44.51) and 37.96% (95% CI: 32.81–43.40), respectively. For rubella, the positivity rate in the precampaign season was 21.73% (95% CI: 19.61–23.99) and in the postvaccination season was 6.65% (95% CI: 4.36–10.00). Binomial tests indicated that postcampaign positivity rates were significantly lower than the precampaign rate for measles ( $p=0.003$ ) and rubella ( $p<0.001$ ). Generally, age (χ2 = 58.94, $p=0.001$ /χ2 = 51.91, $p<0.001$ ) and vaccination status (χ2 = 60.48, $p=0.001$ /χ2 = 16.90, $p=0.001$ ) were associated with the measles positivity rate in both pre/postcampaign periods. Rubella positivity rate was associated with vaccination status (χ2 = 32.97, $p<0.001$ / $p=0.001$ ) in both periods and age in the precampaign season ( $p<0.001$ ). The measles-rubella mass campaign lessened rubella burden remarkably, but barely adequate change was observed in the extent of spread of measles. Children aged less than 9 months are at higher chances of testing positive amidst low vaccination levels among the eligible. The immunization programme must attain and maintain routine immunization coverage at 95% or more and roll out a second-dose measles-rubella vaccination to sustain the reduced disease burden.

Epidemiology of floods in sub-Saharan Africa: a systematic review of health outcomes

BACKGROUND

Floods have affected 2.3 billion people worldwide in the last 20 years, and are associated with a wide range of negative health outcomes. Climate change is projected to increase the number of people exposed to floods due to more variable precipitation and rising sea levels. Vulnerability to floods is highly dependent on economic wellbeing and other societal factors. Therefore, this systematic review synthesizes the evidence on health effects of flood exposure among the population of sub-Saharan Africa.

METHODS

We systematically searched two databases, Web of Science and PubMed, to find published articles. We included studies that (1) were published in English from 2010 onwards, (2) presented associations between flood exposure and health indicators, (3) focused on sub-Saharan Africa, and (4) relied on a controlled study design, such as cohort studies, case-control studies, cross-sectional studies, or quasi-experimental approaches with a suitable comparator, for instance individuals who were not exposed to or affected by floods or individuals prior to experiencing a flood.

RESULTS

Out of 2306 screened records, ten studies met our eligibility criteria. We included studies that reported the impact of floods on water-borne diseases (n = 1), vector-borne diseases (n = 8) and zoonotic diseases (n = 1). Five of the ten studies assessed the connection between flood exposure and malaria. One of these five evaluated the impact of flood exposure on malaria co-infections. The five non-malaria studies focused on cholera, scabies, taeniasis, Rhodesian sleeping sickness, alphaviruses and flaviviruses. Nine of the ten studies reported significant increases in disease susceptibility after flood exposure.

CONCLUSION

The majority of included studies of the aftermath of floods pointed to an increased risk of infection with cholera, scabies, taeniasis, Rhodesian sleeping sickness, malaria, alphaviruses and flaviviruses. However, long-term health effects, specifically on mental health, non-communicable diseases and pregnancy, remain understudied. Further research is urgently needed to improve our understanding of the health risks associated with floods, which will inform public policies to prevent and reduce flood-related health risks.

Relationships between test positivity rate, total laboratory confirmed cases of malaria, and malaria incidence in high burden settings of Uganda: an ecological analysis

BACKGROUND

Malaria surveillance is critical for monitoring changes in malaria morbidity over time. National Malaria Control Programmes often rely on surrogate measures of malaria incidence, including the test positivity rate (TPR) and total laboratory confirmed cases of malaria (TCM), to monitor trends in malaria morbidity. However, there are limited data on the accuracy of TPR and TCM for predicting temporal changes in malaria incidence, especially in high burden settings.

METHODS

This study leveraged data from 5 malaria reference centres (MRCs) located in high burden settings over a 15-month period from November 2018 through January 2020 as part of an enhanced health facility-based surveillance system established in Uganda. Individual level data were collected from all outpatients including demographics, laboratory test results, and village of residence. Estimates of malaria incidence were derived from catchment areas around the MRCs. Temporal relationships between monthly aggregate measures of TPR and TCM relative to estimates of malaria incidence were examined using linear and exponential regression models.

RESULTS

A total of 149,739 outpatient visits to the 5 MRCs were recorded. Overall, malaria was suspected in 73.4% of visits, 99.1% of patients with suspected malaria received a diagnostic test, and 69.7% of those tested for malaria were positive. Temporal correlations between monthly measures of TPR and malaria incidence using linear and exponential regression models were relatively poor, with small changes in TPR frequently associated with large changes in malaria incidence. Linear regression models of temporal changes in TCM provided the most parsimonious and accurate predictor of changes in malaria incidence, with adjusted R² values ranging from 0.81 to 0.98 across the 5 MRCs. However, the slope of the regression lines indicating the change in malaria incidence per unit change in TCM varied from 0.57 to 2.13 across the 5 MRCs, and when combining data across all 5 sites, the R² value reduced to 0.38.

CONCLUSIONS

In high malaria burden areas of Uganda, site-specific temporal changes in TCM had a strong linear relationship with malaria incidence and were a more useful metric than TPR. However, caution should be taken when comparing changes in TCM across sites.

Malaria micro-stratification using routine surveillance data in Western Kenya

BACKGROUND

There is an increasing need for finer spatial resolution data on malaria risk to provide micro-stratification to guide sub-national strategic plans. Here, spatial-statistical techniques are used to exploit routine data to depict sub-national heterogeneities in test positivity rate (TPR) for malaria among patients attending health facilities in Kenya.

METHODS

Routine data from health facilities (n = 1804) representing all ages over 24 months (2018-2019) were assembled across 8 counties (62 sub-counties) in Western Kenya. Statistical model-based approaches were used to quantify heterogeneities in TPR and uncertainty at fine spatial resolution adjusting for missingness, population distribution, spatial data structure, month, and type of health facility.

RESULTS

The overall monthly reporting rate was 78.7% (IQR 75.0-100.0) and public-based health facilities were more likely than private facilities to report ≥ 12 months (OR 5.7, 95% CI 4.3-7.5). There was marked heterogeneity in population-weighted TPR with sub-counties in the north of the lake-endemic region exhibiting the highest rates (exceedance probability > 70% with 90% certainty) where approximately 2.7 million (28.5%) people reside. At micro-level the lowest rates were in 14 sub-counties (exceedance probability < 30% with 90% certainty) where approximately 2.2 million (23.1%) people lived and indoor residual spraying had been conducted since 2017.

CONCLUSION

The value of routine health data on TPR can be enhanced when adjusting for underlying population and spatial structures of the data, highlighting small-scale heterogeneities in malaria risk often masked in broad national stratifications. Future research should aim at relating these heterogeneities in TPR with traditional community-level prevalence to improve tailoring malaria control activities at sub-national levels.

A Model for Assessing the Quantitative Effects of Heterogeneous Affinity in Malaria Transmission along with Ivermectin Mass Administration

Using an agent-based model of malaria, we present numerical evidence that in communities of individuals having an affinity varying within a broad range of values, disease transmission may increase up to 300%. Moreover, our findings provide new insight into how to combine different strategies for the prevention of malaria transmission. In particular, we uncover a relationship between the level of heterogeneity and the level of conventional and unconventional anti-malarial drug administration (ivermectin and gametocidal agents), which, when taken together, will define a control parameter, tuning between disease persistence and elimination. Finally, we also provide evidence that the entomological inoculation rate, as well as the product between parasite and sporozoite rates are both good indicators of malaria incidence in the presence of heterogeneity in disease transmission and may configure a possible improvement in that setting, upon classical standard measures such as the basic reproductive number.

Estimating malaria incidence from routine health facility-based surveillance data in Uganda

Background

Accurate measures of malaria incidence are essential to track progress and target high-risk populations. While health management information system (HMIS) data provide counts of malaria cases, quantifying the denominator for incidence using these data is challenging because catchment areas and care-seeking behaviours are not well defined. This study’s aim was to estimate malaria incidence using HMIS data by adjusting the population denominator accounting for travel time to the health facility.

Methods

Outpatient data from two public health facilities in Uganda (Kihihi and Nagongera) over a 3-year period (2011–2014) were used to model the relationship between travel time from patient village of residence (available for each individual) to the facility and the relative probability of attendance using Poisson generalized additive models. Outputs from the model were used to generate a weighted population denominator for each health facility and estimate malaria incidence. Among children aged 6 months to 11 years, monthly HMIS-derived incidence estimates, with and without population denominators weighted by probability of attendance, were compared with gold standard measures of malaria incidence measured in prospective cohorts.

Results

A total of 48,898 outpatient visits were recorded across the two sites over the study period. HMIS incidence correlated with cohort incidence over time at both study sites (correlation in Kihihi = 0.64, p < 0.001; correlation in Nagongera = 0.34, p = 0.045). HMIS incidence measures with denominators unweighted by probability of attendance underestimated cohort incidence aggregated over the 3 years in Kihihi (0.5 cases per person-year (PPY) vs 1.7 cases PPY) and Nagongera (0.3 cases PPY vs 3.0 cases PPY). HMIS incidence measures with denominators weighted by probability of attendance were closer to cohort incidence, but remained underestimates (1.1 cases PPY in Kihihi and 1.4 cases PPY in Nagongera).

Conclusions

Although malaria incidence measured using HMIS underestimated incidence measured in cohorts, even when adjusting for probability of attendance, HMIS surveillance data are a promising and scalable source for tracking relative changes in malaria incidence over time, particularly when the population denominator can be estimated by incorporating information on village of residence.

Malaria smear positivity among Kenyan children peaks at intermediate temperatures as predicted by ecological models

Background

Ambient temperature is an important determinant of malaria transmission and suitability, affecting the life-cycle of the Plasmodium parasite and Anopheles vector. Early models predicted a thermal malaria transmission optimum of 31 °C, later revised to 25 °C using experimental data from mosquito and parasite biology. However, the link between ambient temperature and human malaria incidence remains poorly resolved.

Methods

To evaluate the relationship between ambient temperature and malaria risk, 5833 febrile children (<18 years-old) with an acute, non-localizing febrile illness were enrolled from four heterogenous outpatient clinic sites in Kenya (Chulaimbo, Kisumu, Msambweni and Ukunda). Thick and thin blood smears were evaluated for the presence of malaria parasites. Daily temperature estimates were obtained from land logger data, and rainfall from National Oceanic and Atmospheric Administration (NOAA)’s Africa Rainfall Climatology (ARC) data. Thirty-day mean temperature and 30-day cumulative rainfall were estimated and each lagged by 30 days, relative to the febrile visit. A generalized linear mixed model was used to assess relationships between malaria smear positivity and predictors including temperature, rainfall, age, sex, mosquito exposure and socioeconomic status.

Results

Malaria smear positivity varied between 42–83% across four clinic sites in western and coastal Kenya, with highest smear positivity in the rural, western site. The temperature ranges were cooler in the western sites and warmer in the coastal sites. In multivariate analysis controlling for socioeconomic status, age, sex, rainfall and bednet use, malaria smear positivity peaked near 25 °C at all four sites, as predicted a priori from an ecological model.

Conclusions

This study provides direct field evidence of a unimodal relationship between ambient temperature and human malaria incidence with a peak in malaria transmission occurring at lower temperatures than previously recognized clinically. This nonlinear relationship with an intermediate optimal temperature implies that future climate warming could expand malaria incidence in cooler, highland regions while decreasing incidence in already warm regions with average temperatures above 25 °C. These findings support efforts to further understand the nonlinear association between ambient temperature and vector-borne diseases to better allocate resources and respond to disease threats in a future, warmer world.

Electronic supplementary material

The online version of this article (10.1186/s13071-019-3547-z) contains supplementary material, which is available to authorized users.

Impact of the 2013 Floods on the Incidence of Malaria in Almanagil Locality, Gezira State, Sudan

Background: Heavy rain hit Sudan in August 2013 with subsequent flash floods in different parts of the country. This study investigated the impact of the flooding on incidence of malaria in Almanagil Locality in central Sudan.

Methods: This observational retrospective study compared malaria data sets during rainfall seasons in the Almanagil Locality in the year of flooding (2013) with those of corresponding rainfall seasons of previous two non-flood years (2011 and 2012).

Results: A marked increase of new malaria cases and incidence rate was observed in the 13 sentinel malaria notification sites in the locality  (IR increased from 6.09 per 100,000 person­days in 2011 [95 % CI: 5.93-6.26] and 6.48 in 2012 [95 % CI: 6.31-6.65] to 8.24 in 2013 [95 % CI: 8.05-8.43] ; P< 0.0001), with a peaking of the incidence rate in the under-5-years age group (IR for this age group jumped from 9.80 per 100,000 person­days in 2011 [95 % CI: 9.29­10.32] and 10.00 in 2012 [95 % CI: 9.52­10.49] to 15.02 in 2013 [95 % CI: 14.41­15.64]). A noticeable increase in the slide positivity rate (P< 0.0001) was observed in the 12-week period of 2013 (SPR = 20.86% [95 % CI: 20.40 ­21.32%]) compared with the same periods in 2011 (SPR = 8.72% [95 % CI: 8.36 ­9.08%]) and 2012 (SPR = 12.62% [95 % CI: 12.24 ­13.01%]), with a more marked rise of the SPR in the under-5-year age group. Hospital data showed increase in both the inpatient and outpatient incidence proportions in the study period of 2013 compared to those of the years 2011 and 2012. Hospital OPD incidence proportion in 2013 was 19.7% (95% CI: 19.24­20.18%) compared to 12.85% (95% CI: 12.48­13.23%) in 2011, and 12.16% (95% CI: 11.82­12.51%) in 2012. The < 5 year old groups were responsible for the overall rise in the proportion of malaria cases in 2013 , particularly the < 1 year old group which more than doubled in the 2013 period compared to both 2011 and 2012 periods (Age­specific proportion of the outpatient malaria cases of the < 1 year old group in 2013 was19.5% [95% CI: 18.5­20.6%]  compared to 7.7% [95% CI: 6.9­8.6%] in 2011 and 8.1% [95% CI: 7.3­8.9%] in 2012. Incidence proportion of severe malaria cases (inpatients) increased to 22.5 % (95 % CI: 21.5 to 23.6 %) in the study period of 2013 compared to 19.8 % (95 % CI: 18.6 to 21.0 %) in 2011 and 18.4 % (95 % CI: 17.4 to 19.5) in 2012. The increase in the proportion of severe malaria cases was mainly due to a higher proportion of children < 5 years of age and especially to a higher proportion of children < 1 year of age.

Conclusion: The study revealed a significant increase in the incidence rate of malaria in Almanagil Locality following the flash flood of August 2013. The flooding had the highest impact on the malaria incidence of the under-5-years age group, and particularly of the under-1-year age group.

Keywords: Flood, Flooding, Malaria, Disaster, Sudan, Gezira, Almanagil

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.

Bayesian spatio-temporal modeling of mortality in relation to malaria incidence in Western Kenya

INTRODUCTION

The effect of malaria exposure on mortality using health facility incidence data as a measure of transmission has not been well investigated. Health and demographic surveillance systems (HDSS) routinely capture data on mortality, interventions and other household related indicators, offering a unique platform for estimating and monitoring the incidence-mortality relationship in space and time.

METHODS

Mortality data from the HDSS located in Western Kenya collected from 2007 to 2012 and linked to health facility incidence data were analysed using Bayesian spatio-temporal survival models to investigate the relation between mortality (all-cause/malaria-specific) and malaria incidence across all age groups. The analysis adjusted for insecticide-treated net (ITN) ownership, socio-economic status (SES), distance to health facilities and altitude. The estimates obtained were used to quantify excess mortality due to malaria exposure.

RESULTS

Our models identified a strong positive relationship between slide positivity rate (SPR) and all-cause mortality in young children 1-4 years (HR = 4.29; 95% CI: 2.78-13.29) and all ages combined (HR = 1.55; 1.04-2.80). SPR had a strong positive association with malaria-specific mortality in young children (HR = 9.48; 5.11-37.94), however, in older children (5-14 years), it was associated with a reduction in malaria specific mortality (HR = 0.02; 0.003-0.33).

CONCLUSION

SPR as a measure of transmission captures well the association between malaria transmission intensity and all-cause/malaria mortality. This offers a quick and efficient way to monitor malaria burden. Excess mortality estimates indicate that small changes in malaria incidence substantially reduce overall and malaria specific mortality.

Rapid reduction of malaria following introduction of vector control interventions in Tororo District, Uganda: a descriptive study

BACKGROUND

In 2012, Tororo District had the highest malaria burden in Uganda with community Plasmodium prevalence of 48%. To control malaria in the district, the Ministry of Health introduced universal distribution of long lasting insecticide-treated nets (LLINs) in 2013 and added indoor residual spraying (IRS) in 2014. This study assessed malaria incidence, test positivity rates and outpatient (OPD) attendance due to malaria before and after vector control interventions.

METHODS

This study was based on analysis of Health Management Information System (HMIS) secondary malaria surveillance data of 2,727,850 patient records in OPD registers of 61 health facilities from 2012 to 2015. The analysis estimated monthly malaria incidence for the entire population and also separately for <5- and ≥5-year-olds before and after introduction of vector control interventions; determined laboratory test positivity rates and annual percentage of malaria cases in OPD. Chi square for trends was used to analyse annual change in malaria incidence and logistic regression for monthly reduction.

RESULTS

Following universal LLINs coverage, the annual mean monthly malaria incidence fell from 95 cases in 2013 to 76 cases per 1000 in 2014 with no significant monthly reduction (OR = 0.99, 95% CI 0.96-1.01, P = 0.37). Among children <5 years, the malaria incidence reduced from 130 to 100 cases per 1000 (OR = 0.98, 95% CI 0.97-1.00, P = 0.08) when LLINs were used alone in 2014, but declined to 45 per 1000 in 2015 when IRS was combined with LLINs (OR = 0.94, 95% CI 0.91-0.996, P < 0.0001). Among individuals aged ≥5 years, mean monthly malaria incidence reduced from 59 to 52 cases per 1000 (OR = 0.99, 95% CI 0.97-1.02, P = 0.8) when LLINs were used alone in 2014, but reduced significantly to 25 per 1000 in 2015 (OR = 0.91, 95% CI 0.88-0.94, P < 0.0001). Malaria test positivity rate reduced from 57% in 2013 to 30% (Chi = 15, P < 0.0001) in 2015. Slide positivity rate reduced from 45% in 2013 to 21% in 2015 (P = 0.004) while RDT positivity declined from 69 to 40%.

CONCLUSIONS

A rapid reduction in malaria incidence was observed in Tororo District following the introduction of IRS in addition to LLINs. There was no significant reduction in malaria incidence following universal distribution of LLINs to communities before introduction of IRS.

A national health facility survey of malaria infection among febrile patients in Kenya, 2014

BACKGROUND

The use of malaria infection prevalence among febrile patients at clinics has a potential to be a valuable epidemiological surveillance tool. However, routine data are incomplete and not all fevers are tested. This study was designed to screen all fevers for malaria infection in Kenya to explore the epidemiology of fever test positivity rates.

METHODS

Random sampling was used within five malaria epidemiological zones of Kenya (i.e., high lake endemic, moderate coast endemic, highland epidemic, seasonal low transmission and low risk zones). The selected sample was representative of the number of hospitals, health centres and dispensaries within each zone. Fifty patients with fever presenting to each sampled health facility during the short rainy season were screened for malaria infection using a rapid diagnostic test (RDT). Details of age, pregnancy status and basic demographics were recorded for each patient screened.

RESULTS

10,557 febrile patients presenting to out-patient clinics at 234 health facilities were screened for malaria infection. 1633 (15.5%) of the patients surveyed were RDT positive for malaria at 124 (53.0%) facilities. Infection prevalence among non-pregnant patients varied between malaria risk zones, ranging from 0.6% in the low risk zone to 41.6% in the high lake endemic zone. Test positivity rates (TPR) by age group reflected the differences in the intensity of transmission between epidemiological zones. In the lake endemic zone, 6% of all infections were among children aged less than 1 year, compared to 3% in the coast endemic, 1% in the highland epidemic zone, less than 1% in the seasonal low transmission zone and 0% in the low risk zone. Test positivity rate was 31% among febrile pregnant women in the high lake endemic zone compared to 9% in the coast endemic and highland epidemic zones, 3.2% in the seasonal low transmission zone and zero in the low risk zone.

CONCLUSION

Malaria infection rates among febrile patients, with supporting data on age and pregnancy status presenting to clinics in Kenya can provide invaluable epidemiological data on spatial heterogeneity of malaria and serve as replacements to more expensive community-based infection rates to plan and monitor malaria control.

Measures of Malaria Burden after Long-Lasting Insecticidal Net Distribution and Indoor Residual Spraying at Three Sites in Uganda: A Prospective Observational Study

BACKGROUND

Long-lasting insecticidal nets (LLINs) and indoor residual spraying of insecticide (IRS) are the primary vector control interventions used to prevent malaria in Africa. Although both interventions are effective in some settings, high-quality evidence is rarely available to evaluate their effectiveness following deployment by a national malaria control program. In Uganda, we measured changes in key malaria indicators following universal LLIN distribution in three sites, with the addition of IRS at one of these sites.

METHODS AND FINDINGS

Comprehensive malaria surveillance was conducted from October 1, 2011, to March 31, 2016, in three sub-counties with relatively low (Walukuba), moderate (Kihihi), and high transmission (Nagongera). Between 2013 and 2014, universal LLIN distribution campaigns were conducted in all sites, and in December 2014, IRS with the carbamate bendiocarb was initiated in Nagongera. High-quality surveillance evaluated malaria metrics and mosquito exposure before and after interventions through (a) enhanced health-facility-based surveillance to estimate malaria test positivity rate (TPR), expressed as the number testing positive for malaria/number tested for malaria (number of children tested for malaria: Walukuba = 42,833, Kihihi = 28,790, and Nagongera = 38,690); (b) cohort studies to estimate the incidence of malaria, expressed as the number of episodes per person-year [PPY] at risk (number of children observed: Walukuba = 340, Kihihi = 380, and Nagongera = 361); and (c) entomology surveys to estimate household-level human biting rate (HBR), expressed as the number of female Anopheles mosquitoes collected per house-night of collection (number of households observed: Walukuba = 117, Kihihi = 107, and Nagongera = 107). The LLIN distribution campaign substantially increased LLIN coverage levels at the three sites to between 65.0% and 95.5% of households with at least one LLIN. In Walukuba, over the 28-mo post-intervention period, universal LLIN distribution was associated with no change in the incidence of malaria (0.39 episodes PPY pre-intervention versus 0.20 post-intervention; adjusted rate ratio [aRR] = 1.02, 95% CI 0.36-2.91, p = 0.97) and non-significant reductions in the TPR (26.5% pre-intervention versus 26.2% post-intervention; aRR = 0.70, 95% CI 0.46-1.06, p = 0.09) and HBR (1.07 mosquitoes per house-night pre-intervention versus 0.71 post-intervention; aRR = 0.41, 95% CI 0.14-1.18, p = 0.10). In Kihihi, over the 21-mo post-intervention period, universal LLIN distribution was associated with a reduction in the incidence of malaria (1.77 pre-intervention versus 1.89 post-intervention; aRR = 0.65, 95% CI 0.43-0.98, p = 0.04) but no significant change in the TPR (49.3% pre-intervention versus 45.9% post-intervention; aRR = 0.83, 95% 0.58-1.18, p = 0.30) or HBR (4.06 pre-intervention versus 2.44 post-intervention; aRR = 0.71, 95% CI 0.30-1.64, p = 0.40). In Nagongera, over the 12-mo post-intervention period, universal LLIN distribution was associated with a reduction in the TPR (45.3% pre-intervention versus 36.5% post-intervention; aRR = 0.82, 95% CI 0.76-0.88, p < 0.001) but no significant change in the incidence of malaria (2.82 pre-intervention versus 3.28 post-intervention; aRR = 1.10, 95% 0.76-1.59, p = 0.60) or HBR (41.04 pre-intervention versus 20.15 post-intervention; aRR = 0.87, 95% CI 0.31-2.47, p = 0.80). The addition of three rounds of IRS at ~6-mo intervals in Nagongera was followed by clear decreases in all outcomes: incidence of malaria (3.25 pre-intervention versus 0.63 post-intervention; aRR = 0.13, 95% CI 0.07-0.27, p < 0.001), TPR (37.8% pre-intervention versus 15.0% post-intervention; aRR = 0.54, 95% CI 0.49-0.60, p < 0.001), and HBR (18.71 pre-intervention versus 3.23 post-intervention; aRR = 0.29, 95% CI 0.17-0.50, p < 0.001). High levels of pyrethroid resistance were documented at all three study sites. Limitations of the study included the observational study design, the lack of contemporaneous control groups, and that the interventions were implemented under programmatic conditions.

CONCLUSIONS

Universal distribution of LLINs at three sites with varying transmission intensity was associated with modest declines in the burden of malaria for some indicators, but the addition of IRS at the highest transmission site was associated with a marked decline in the burden of malaria for all indicators. In highly endemic areas of Africa with widespread pyrethroid resistance, IRS using alternative insecticide formulations may be needed to achieve substantial gains in malaria control.

Practical Implications of the Non-Linear Relationship between the Test Positivity Rate and Malaria Incidence

Background

The test positivity rate (TPR), defined as the number of laboratory-confirmed malaria tests per 100 suspected cases examined, is widely used by malaria surveillance programs as one of several key indicators of temporal trends in malaria incidence. However, there have been few studies using empiric data to examine the quantitative nature of this relationship.

Methods

To characterize the relationship between the test positivity rate and the incidence of malaria, we fit regression models using the confirmed malaria case rate as the outcome of interest and TPR as the predictor of interest. We varied the relationship between the two by alternating linear and polynomial terms for TPR, and compared the goodness of fit of each model.

Results

A total of 7,668 encounters for malaria diagnostic testing were recorded over the study period within a catchment area of 25,617 persons. The semi-annual TPR ranged from 4.5% to 59% and the case rates ranged from 0.5 to 560 per 1,000 persons. The best fitting model was an exponential growth model (R² = 0.80, AIC = 637). At low transmission levels (TPR<10%), the correlation between TPR and CMCR was poor, with large reductions in the TPR, for example from 10% to 1%, was associated with a minimal change in the CMCR (3.9 to 1.7 cases per 1,000 persons). At higher transmission levels, the exponential relationship made relatively small changes in TPR suggestive of sizeable change in estimated malaria incidence, suggesting that TPR remains a valuable surveillance indicator in such settings.

Conclusions

The TPR and the confirmed malaria case rate have a non-linear relationship, which is likely to have important implications for malaria surveillance programs, especially at the extremes of transmission.

Spatial heterogeneity of malaria in Ghana: a cross-sectional study on the association between urbanicity and the acquisition of immunity

Background

Malaria incidence has declined considerably over the last decade. This is partly due to a scale-up of control measures but is also attributed to increasing urbanization. This study aimed to analyse the association between malaria and urbanization and the effect of urbanicity on the acquisition of semi-immunity.

Methods

In 2012, children with fever presenting to St Michael’s Hospital Pramso/Ghana were recruited. The malaria-positive-fraction (MPF) of fever cases was calculated on community-level to approximate the malaria risk. The mean age of malaria cases was calculated for each community to estimate the acquisition of semi-immunity. The level of urbanicity for the communities was calculated and associations between MPF, urbanicity and immunity were modelled using linear regression.

Results

Twenty-six villages were included into the study with a mean MPF of 35 %. A linear decrease of 5 % (95 % CI: 4–6 %) in MPF with every ten-point increase in urbanicity was identified. The mean age of malaria patients increased by 2.9 months (95 % CI: 1.0–4.8) with every ten-point increase in urbanicity.

Discussion

The results confirm an association between an increase in urbanicity and declining malaria risk and demonstrate that the acquisition of semi-immunity is heterogeneous on a micro-epidemiological scale and is associated with urbanicity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-016-1138-4) contains supplementary material, which is available to authorized users.

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.

Narrative review of current context of malaria and management strategies in Uganda (Part I)

In accordance with international targets, the Uganda National Malaria Control Strategic Plan established specific targets to be achieved by 2010. For children under five, this included increasing the number of children sleeping under mosquito nets and those receiving a first-line antimalarial to 85%, and decreasing case fatality to 2%. This narrative review offers contextual information relevant to malaria management in Uganda since the advent of artemisinin combination therapy (ACT) as first-line antimalarial treatment in 2004. A comprehensive search using key words and phrases was conducted using the web search engines Google and Google Scholar, as well as the databases of PubMed, ERIC, EMBASE, CINAHL, OvidSP (MEDLINE), PSYC Info, Springer Link, Cochrane Central Register of Controlled Trials (CENTRAL), and Cochrane Database of Systematic Reviews were searched. A total of 147 relevant international and Ugandan literature sources meeting the inclusion criteria were included. This review provides an insightful understanding on six topic areas: global and local priorities, malarial pathology, disease burden, malaria control, treatment guidelines for uncomplicated malaria, and role of the health system in accessing antimalarial medicines. Plasmodium falciparum remains the most common cause of malaria in Uganda, with children under five being most vulnerable due to their underdeveloped immunity. While international efforts to scale up malaria control measures have resulted in considerable decline in malaria incidence and mortality in several regions of sub-Saharan Africa, this benefit has yet to be substantiated for Uganda. At the local level, key initiatives have included implementation of a new antimalarial drug policy in 2004 and strengthening of government health systems and programs. Examples of such programs include removal of user fees, training of frontline health workers, providing free ACT from government systems and subsidized ACT from licensed private outlets, and introduction of the integrated community case management program to bring diagnostics and treatment for malaria, pneumonia and diarrhea closer to the community. However despite notable efforts, Uganda is far from achieving its 2010 targets. Several challenges in the delivery of care and treatment remain, with those most vulnerable and living in rural settings remaining at greatest risk from malaria morbidity and mortality.

Malaria care in infants aged under six months in Uganda: an area of unmet needs!

BACKGROUND

Little information exists on malaria burden, artemisinin-based combination therapy (ACT) use, and malaria care provided to infants under six months of age. The perception that malaria may be rare in this age group has led to lack of clinical trials and evidence-based treatment guidelines. The objective of this study was to identify malaria parasitemia positivity rate (MPPR) among patients under six months, and practices and predictors of malaria diagnosis and treatment in this population.

METHODS

Cross-sectional data collected from October 2010 to September 2011 on 25,997 individual outpatients aged <6 months from 36 health facilities across Uganda were analysed.

FINDINGS

Malaria was suspected in 18,415 (70.8%) patients, of whom 7,785 (42.3%) were tested for malaria. Of those tested, the MPPR was 36.1%, with 63.9% testing negative, of which 1,545 (31.1%) were prescribed an antimalarial. Among children <5kgs, off-label prescription of ACT was high (104/285, 36.5%). Younger age (1-6 days, aOR=0.47, p=0.01; 7-31 days, aOR=0.43, p<0.001; and 1-2 months, aOR=0.61, p<0.001), pneumonia (aOR=0.78, p=0.01) or cough/cold (aOR=0.65, p<0.001) diagnosis, and fever (aOR=0.56, p=0.01) reduced the odds of receiving a malaria test. Fever (aOR=2.22, p<0.001), anemia diagnosis (aOR=3.51, p=0.01), consulting midwives (aOR=3.58, p=0.04) and other less skilled providers (aOR=4.75, p<0.001) relative to medical officers, consulting at hospitals (aOR=3.31, p=0.03), visiting health facilities in a medium-high malaria transmission area (aOR=2.20, p<0.001), and visiting during antimalarial (aOR=1.82, p=0.04) or antibiotic (aOR=2.23, p=0.04) shortages increased the odds of prescribing an antimalarial despite a negative malaria test result.

CONCLUSIONS

We found high malaria suspicion but low testing rates in outpatient children aged <6 months. Among those tested, MPPR was high. Despite a negative malaria test result, many infants were prescribed antimalarials. Off-label ACT prescription was common in children weighing <5kgs. Evidence-based malaria guidelines for infants weighing <5 kilograms and aged <6 months are urgently needed.

Pfcrt Gene in Plasmodium falciparum Field Isolates from Muzaffargarh, Pakistan

BACKGROUND

The aim of the study was to identify the prevalence of different species of Plasmodium and haplotypes of pfcrt in Plasmodium falciparum from the selected area.

METHODS

Overall, 10,372 blood films of suspected malarial patients were examined microscopically from rural health center Sinawan, district Muzaffargarh, Pakistan from November 2008 to November 2010. P. falciparum positive samples (both whole blood and FTA blood spotted cards) were used for DNA extraction. Nested PCR was used to amplify the pfcrt (codon 72-76) gene fragment. Sequencing was carried out to find the haplotypes in the amplified fragment of pfcrt gene.

RESULT

Over all slide positivity rate (SPR), P. vivax and P. falciparum positivity rate was 21.40 %, 19.37 % and 2.03% respectively. FTA blood spotted cards were equally efficient in the blood storage for PCR and sequencing. Analysis of sequencing results of pfcrt showed only one type of haplotype SagtVMNT (AGTGTAATGAATACA) from codon 72-76 in all samples.

CONCLUSION

The results show high prevalence of CQ resistance and AQ resistant genes. AQ is not recommended to be used as a partner drug in ACT in this locality, so as to ward off future catastrophes.

Malaria in the Americas: trends from 1959 to 2011

Malaria has declined in recent years in countries of the American continents. In 2011, 12 of 21 endemic countries had already met their 2015 Millennium Development Goal. However, this declining trend has not been adequately evaluated. An analysis of the number of cases per 100,000 people (annual parasite index [API]) and the percentage of positive blood slides (slide positivity rate [SPR]) during the period of 1959-2011 in 21 endemic countries was done using the joinpoint regression methodology. During 1960-1979, API and SPR increased significantly and peaked in the 1980s. Since the 1990s, there have been significant declining trends in both API and SPR. Additionally, both Plasmodium vivax and P. falciparum species-specific incidence have declined. With the exception of two countries, such a collectively declining malaria trend was not observed in previous decades. This presents a unique opportunity for the Americas to seriously consider malaria elimination as a final goal.

A micro-epidemiological analysis of febrile malaria in Coastal Kenya showing hotspots within hotspots

Malaria transmission is spatially heterogeneous. This reduces the efficacy of control strategies, but focusing control strategies on clusters or 'hotspots' of transmission may be highly effective. Among 1500 homesteads in coastal Kenya we calculated (a) the fraction of febrile children with positive malaria smears per homestead, and (b) the mean age of children with malaria per homestead. These two measures were inversely correlated, indicating that children in homesteads at higher transmission acquire immunity more rapidly. This inverse correlation increased gradually with increasing spatial scale of analysis, and hotspots of febrile malaria were identified at every scale. We found hotspots within hotspots, down to the level of an individual homestead. Febrile malaria hotspots were temporally unstable, but 4 km radius hotspots could be targeted for 1 month following 1 month periods of surveillance.DOI: http://dx.doi.org/10.7554/eLife.02130.001.

Measuring changes in Plasmodium falciparum transmission: precision, accuracy and costs of metrics

As malaria declines in parts of Africa and elsewhere, and as more countries move towards elimination, it is necessary to robustly evaluate the effect of interventions and control programmes on malaria transmission. To help guide the appropriate design of trials to evaluate transmission-reducing interventions, we review 11 metrics of malaria transmission, discussing their accuracy, precision, collection methods and costs and presenting an overall critique. We also review the nonlinear scaling relationships between five metrics of malaria transmission: the entomological inoculation rate, force of infection, sporozoite rate, parasite rate and the basic reproductive number, R0. Our chapter highlights that while the entomological inoculation rate is widely considered the gold standard metric of malaria transmission and may be necessary for measuring changes in transmission in highly endemic areas, it has limited precision and accuracy and more standardised methods for its collection are required. In areas of low transmission, parasite rate, seroconversion rates and molecular metrics including MOI and mFOI may be most appropriate. When assessing a specific intervention, the most relevant effects will be detected by examining the metrics most directly affected by that intervention. Future work should aim to better quantify the precision and accuracy of malaria metrics and to improve methods for their collection.

Factoring quality laboratory diagnosis into the malaria control agenda for sub-Saharan Africa

Recent progress in malaria control in sub-Saharan Africa has been achieved primarily through provision of insecticide-treated nets, indoor residual spraying, and antimalarial drugs. Although these interventions are important, proper case identification and accurate measurement of their impact depend on quality diagnostic testing. Current availability of diagnostic testing for malaria in sub-Saharan Africa is inadequate to support disease management, prevention programs, and surveillance needs. Challenges faced include a dearth of skilled workforce, inadequate health systems infrastructure, and lack of political will. A coordinated approach to providing pre-service clinical and laboratory training together with systems that support a scale-up of laboratory services could provide means not only for effective malaria case management but also, management of non-malaria febrile illnesses, disease surveillance, and accurate control program evaluation. A synthesis of the challenges faced in ensuring quality malaria testing and how to include this information in the malaria control and elimination agenda are presented.

Indoor residual spraying of insecticide and malaria morbidity in a high transmission intensity area of Uganda

Background

Recently the use of indoor residual spraying of insecticide (IRS) has greatly increased in Africa; however, limited data exist on the quantitative impacts of IRS on health outcomes in highly malaria endemic areas.

Methodology/Principal Findings

Routine data were collected on more than 90,000 patient visits at a single health facility over a 56 month period covering five rounds of IRS using three different insecticides. Temporal associations between the timing of IRS and the probability of a patient referred for microscopy having laboratory confirmed malaria were estimated controlling for seasonality and age. Considering patients less than five years of age there was a modest decrease in the odds of malaria following the 1^st round of IRS using DDT (OR = 0.76, p<0.001) and the 2^nd round using alpha-cypermethrin (OR = 0.83, p = 0.002). Following rounds 3–5 using bendiocarb there was a much greater decrease in the odds of malaria (ORs 0.34, 0.16, 0.17 respectively, p<0.001 for all comparisons). Overall, the impact of IRS was less pronounced among patients 5 years or older.

Conclusions/Significance

IRS was associated with a reduction in malaria morbidity in an area of high transmission intensity in Uganda and the benefits appeared to be greatest after switching to a carbamate class of insecticide.

Health facility-based malaria surveillance: the effects of age, area of residence and diagnostics on test positivity rates

Background

The malaria test positivity rate (TPR) is increasingly used as an indicator of malaria morbidity because TPR is based on laboratory-confirmed cases and is simple to incorporate into existing surveillance systems. However, temporal trends in TPR may reflect changes in factors associated with malaria rather than true changes in malaria morbidity. This study examines the effects of age, area of residence and diagnostic test on TPR at two health facilities in regions of Uganda with differing malaria endemicity.

Methods

The analysis included data from diagnostic blood smears performed at health facilities in Walukuba and Aduku between January 2009 and December 2010. The associations between age and time and between age and TPR were evaluated independently to determine the potential for age to confound temporal trends in TPR. Subsequently, differences between observed TPR and TPR adjusted for age were compared to determine if confounding was present. A similar analysis was performed for area of residence. Temporal trends in observed TPR were compared to trends in TPR expected using rapid diagnostic tests, which were modelled based upon sensitivity and specificity in prior studies.

Results

Age was independently associated with both TPR and time at both sites. At Aduku, age-adjusted TPR increased relative to observed TPR due to the association between younger age and TPR and the gradual increase in age distribution. At Walukuba, there were no clear differences between observed and age-adjusted TPR. Area of residence was independently associated with both TPR and time at both sites, though there were no clear differences in temporal trends in area of residence-adjusted TPR and observed TPR at either site. Expected TPR with pLDH- and HRP-2-based rapid diagnostic tests (RDTs) was higher than observed TPR at all time points at both sites.

Conclusions

Adjusting for potential confounders such as age and area of residence can ensure that temporal trends in TPR due to confounding are not mistakenly ascribed to true changes in malaria morbidity. The potentially large effect of diagnostic test on TPR can be accounted for by calculating and adjusting for the sensitivity and specificity of the test used.

Can slide positivity rates predict malaria transmission?

BACKGROUND

Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan Province, China.

METHODS

Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC) and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence.

RESULTS

The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (β = 1.244, p = 0.000) alone and combination (SPR, β = 1.326, p < 0.001) with other predictors can explain about 85% and 95% of variation in malaria transmission, respectively. Every 1% increase in SPR corresponded to an increase of 1.76/100,000 in malaria incidence rates.

CONCLUSION

SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.

A refined estimate of the malaria burden in Niger

Background

The health authorities of Niger have implemented several malaria prevention and control programmes in recent years. These interventions broadly follow WHO guidelines and international recommendations and are based on interventions that have proved successful in other parts of Africa. Most performance indicators are satisfactory but, paradoxically, despite the mobilization of considerable human and financial resources, the malaria-fighting programme in Niger seems to have stalled, as it has not yet yielded the expected significant decrease in malaria burden. Indeed, the number of malaria cases reported by the National Health Information System has actually increased by a factor of five over the last decade, from about 600,000 in 2000 to about 3,000,000 in 2010. One of the weaknesses of the national reporting system is that the recording of malaria cases is still based on a presumptive diagnosis approach, which overestimates malaria incidence.

Methods

An extensive nationwide survey was carried out to determine by microscopy and RDT testing, the proportion of febrile patients consulting at health facilities for suspected malaria actually suffering from the disease, as a means of assessing the magnitude of this problem and obtaining a better estimate of malaria morbidity in Niger.

Results

In total, 12,576 febrile patients were included in this study; 57% of the slides analysed were positive for the malaria parasite during the rainy season, when transmission rates are high, and 9% of the slides analysed were positive during the dry season, when transmission rates are lower. The replacement of microscopy methods by rapid diagnostic tests resulted in an even lower rate of confirmation, with only 42% of cases testing positive during the rainy season, and 4% during the dry season. Fever alone has a low predictive value, with a low specificity and sensitivity. These data highlight the absolute necessity of confirming all reported malaria cases by biological diagnosis methods, to increase the accuracy of the malaria indicators used in monitoring and evaluation processes and to improve patient care in the more remote areas of Niger. This country extends over a large range of latitudes, resulting in the existence of three major bioclimatic zones determining vector distribution and endemicity.

Conclusion

This survey showed that the number of cases of presumed malaria reported in health centres in Niger is largely overestimated. The results highlight inadequacies in the description of the malaria situation and disease risk in Niger, due to the over-diagnosis of malaria in patients with simple febrile illness. They point out the necessity of confirming all cases of suspected malaria by biological diagnosis methods and the need to take geographic constraints into account more effectively, to improve malaria control and to adapt the choice of diagnostic method to the epidemiological situation in the area concerned. Case confirmation will thus also require a change in behaviour, through the training of healthcare staff, the introduction of quality control, greater supervision of the integrated health centres, the implementation of good clinical practice and a general optimization of the use of available diagnostic methods.

Malaria in Uganda: challenges to control on the long road to elimination: I. Epidemiology and current control efforts

Malaria remains one of the leading health problems of the developing world, and Uganda bears a particularly large burden from the disease. Our understanding is limited by a lack of reliable data, but it is clear that the prevalence of malaria infection, incidence of disease, and mortality from severe malaria all remain very high. Uganda has made progress in implementing key malaria control measures, in particular distribution of insecticide-impregnated bednets, indoor residual spraying of insecticides, utilization of artemisinin-based combination therapy to treat uncomplicated malaria, and provision of intermittent preventive therapy for pregnant women. However, despite enthusiasm regarding the potential for the elimination of malaria in other areas, there is no convincing evidence that the burden of malaria has decreased in Uganda in recent years. Major challenges to malaria control in Uganda include very high malaria transmission intensity, inadequate health care resources, a weak health system, inadequate understanding of malaria epidemiology and the impact of control interventions, increasing resistance of parasites to drugs and of mosquitoes to insecticides, inappropriate case management, inadequate utilization of drugs to prevent malaria, and inadequate epidemic preparedness and response. Despite these challenges, prospects for the control of malaria have improved, and with attention to underlying challenges, progress toward the control of malaria in Uganda can be expected.

External quality assessment of malaria microscopy in the Democratic Republic of the Congo

BACKGROUND

External quality assessments (EQA) are an alternative to cross-checking of blood slides in the quality control of malaria microscopy. This study reports the findings of an EQA of malaria microscopy in the Democratic Republic of the Congo (DRC).

METHODS

After validation, an EQA slide panel and a questionnaire were delivered to diagnostic laboratories in four provinces of DRC. The panel included three samples for diagnosis (sample 1: Plasmodium falciparum, 177,000/μl, sample 2: P. falciparum, 2,500/μl, sample 3: no parasites seen), one didactic sample (Howell-Jolly bodies) and one sample for assessing the quality of staining. Participating laboratories were addressed and selected through the network of the National Tuberculosis Control Programme. Participants were asked to return the responses together with a stained thin and thick blood film for evaluation of Giemsa stain quality.

RESULTS

Among 174 participants (response rate 95.1%), 26.2% scored samples 1, 2 and 3 correctly and 34.3%, 21.5% and 5.8% of participants reported major errors in one, two or three samples respectively. Major errors included reporting "no malaria" or "non-falciparum malaria" for Plasmodium falciparum-positive samples 1 and 2 (16.1% and 34.9% of participants respectively) and "P. falciparum" for Plasmodium negative sample 3 (24.0%). Howell-Jolly bodies (didactic sample) were not recognized by any of the participants but reported as "P. falciparum" by 16.7% of participants. With parasite density expressed according to the "plus system", 16.1% and 21.5% of participants scored one "+" different from the reference score for samples 1 and 2 respectively and 9.7% and 2.9% participants scored more than two "+" different. When expressed as counts of asexual parasites/μl, more than two-thirds of results were outside the mean ± 2SD reference values. The quality of the Giemsa stain was poor, with less than 20% slides complying with all criteria assessed. Only one quarter of participants purchase Giemsa stain from suppliers of documented reliability and half of participants use a buffered staining solution. One third of participants had participated in a formal training about malaria diagnosis, half of them earlier than 2007.

CONCLUSION

The present EQA revealed a poor quality of malaria microscopy in DRC.

Heterogeneous decrease in malaria prevalence in children over a six-year period in south-western Uganda

Background

Malaria is a major public health problem, especially for children. However, recent reports suggest a decline in the malaria burden. The aim of this study was to assess the change in the prevalence of malaria infection among children below five years of age between 2004 and 2010 in a mesoendemic area of Uganda and to analyse the risk factors of malaria infection.

Methods

Two cross-sectional surveys were conducted in 2004 and in 2010 at the end of the rainy and dry seasons to measure the prevalence of P. falciparum infection among children less than five years of age. Rapid diagnostic tests and blood smears were used to diagnose malaria infection. In 2010, sampling was stratified by urban and rural areas. In each selected household, knowledge of malaria and bed nets, and bed net ownership and use, were assessed.

Results

In 2004 and 2010, respectively, a total of 527 and 2,320 (999 in the urban area and 1,321 in rural areas) children less than five years old were enrolled. Prevalence of malaria infection declined from 43% (95% CI: 34-52) in 2004, to 23% (95% CI: 17-30) in rural areas in 2010 and 3% (95% CI: 2-5) in the urban area in 2010. From the rainy to dry season in 2010, prevalence decreased from 23% to 10% (95% CI: 6-14) in rural areas (P = 0.001) and remained stable from 3% to 4% (95% CI: 1-7) in the urban area (P = 0.9). The proportion of households reporting ownership and use of at least one bed net increased from 22.9% in 2004 to 64.7% in the urban area and 44.5% in rural areas in 2010 (P < 0.001). In 2010, the risk of malaria infection was consistently associated with child age and household wealth. In rural areas, malaria infection was also associated with geographic factors.

Conclusions

This study reports a significant drop in the prevalence of malaria infection among children below five years of age, paralleled by an uptake in bed-net use. However, prevalence remains unacceptably high in rural areas and is strongly associated with poverty.

How much remains undetected? Probability of molecular detection of human Plasmodia in the field

Background

In malaria endemic areas, most people are simultaneously infected with different parasite clones. Detection of individual clones is hampered when their densities fluctuate around the detection limit and, in case of P. falciparum, by sequestration during part of their life cycle. This has important implications for measures of levels of infection or for the outcome of clinical trials. This study aimed at measuring the detectability of individual P. falciparum and P. vivax parasite clones in consecutive samples of the same patient and at investigating the impact of sampling strategies on basic epidemiological measures such as multiplicity of infection (MOI).

Methods

Samples were obtained in a repeated cross-sectional field survey in 1 to 4.5 years old children from Papua New Guinea, who were followed up in 2-monthly intervals over 16 months. At each follow-up visit, two consecutive blood samples were collected from each child at intervals of 24 hours. Samples were genotyped for the polymorphic markers msp2 for P. falciparum and msp1F3 and MS16 for P. vivax. Observed prevalence and mean MOI estimated from single samples per host were compared to combined data from sampling twice within 24 h.

Findings and Conclusion

Estimated detectability was high in our data set (0.79 [95% CI 0.76–0.82] for P. falciparum and, depending on the marker, 0.61 [0.58–0.63] or 0.73 [0.71–0.75] for P. vivax). When genotyping data from sequential samples, collected 24 hours apart, were combined, the increase in measured prevalence was moderate, 6 to 9% of all infections were missed on a single day. The effect on observed MOI was more pronounced, 18 to 31% of all individual clones were not detected in a single bleed. Repeated sampling revealed little difference between detectability of P. falciparum and P. vivax.

Rethinking cerebral malaria pathology

PURPOSE OF REVIEW

Intense interventions are ongoing to combat malaria. Malaria mortality investigation remains as an intense area of study with controversies, competing models of pathogenesis, and a few carefully proceeding clinical trials. This review suggests a reframing of the question of cerebral malaria pathology in light of recent findings to focus on dissection of pathogenesis that will lead to effective treatments.

RECENT FINDINGS

Pediatric and adult manifestations of cerebral malaria within the retina allows for intense study of the clinical defined patients including the advent of multiple imaging modalities in endemic regions. Basic pathogenesis in mouse models and human studies, focused on cytokines, inflammation, cytoadherence, and endothelial activation, continues to be elucidated molecule by molecule. Coagulation is variably important and may serve as one of several unifying principles of current pathogenesis models. Parasite-derived molecules - surface or soluble - remain necessary but not sufficient to explain pathologic manifestations.

SUMMARY

As we close the gaps in the fight against global malaria, the question of cerebral malaria mortality remains a source of great concern. We currently have no effective means of reversal of coma or impacting mortality in the comatose patient. As transmission is broken, cerebral malaria will spread to older age groups in Africa where we expect mortality will be higher. Continued directed study of pathogenesis with the primary goal of efficacious interventions in the comatose is a necessity.

An economic evaluation of home management of malaria in Uganda: an interactive Markov model

Background

Home management of malaria (HMM), promoting presumptive treatment of febrile children in the community, is advocated to improve prompt appropriate treatment of malaria in Africa. The cost-effectiveness of HMM is likely to vary widely in different settings and with the antimalarial drugs used. However, no data on the cost-effectiveness of HMM programmes are available.

Methods/Principal Findings

A Markov model was constructed to estimate the cost-effectiveness of HMM as compared to conventional care for febrile illnesses in children without HMM. The model was populated with data from Uganda, but is designed to be interactive, allowing the user to adjust certain parameters, including the antimalarials distributed. The model calculates the cost per disability adjusted life year averted and presents the incremental cost-effectiveness ratio compared to a threshold value. Model output is stratified by level of malaria transmission and the probability that a child would receive appropriate care from a health facility, to indicate the circumstances in which HMM is likely to be cost-effective. The model output suggests that the cost-effectiveness of HMM varies with malaria transmission, the probability of appropriate care, and the drug distributed. Where transmission is high and the probability of appropriate care is limited, HMM is likely to be cost-effective from a provider perspective. Even with the most effective antimalarials, HMM remains an attractive intervention only in areas of high malaria transmission and in medium transmission areas with a lower probability of appropriate care. HMM is generally not cost-effective in low transmission areas, regardless of which antimalarial is distributed. Considering the analysis from the societal perspective decreases the attractiveness of HMM.

Conclusion

Syndromic HMM for children with fever may be a useful strategy for higher transmission settings with limited health care and diagnosis, but is not appropriate for all settings. HMM may need to be tailored to specific settings, accounting for local malaria transmission intensity and availability of health services.