Sample size determination for estimating antibody seroconversion rate under stable malaria transmission intensity

Background In the last decade, several epidemiological studies have demonstrated the potential of using seroprevalence (SP) and seroconversion rate (SCR) as informative indicators of malaria burden in low transmission settings or in populations on the cusp of elimination. However, most of studies are designed to control ensuing statistical inference over parasite rates and not on these alternative malaria burden measures. SP is in essence a proportion and, thus, many methods exist for the respective sample size determination. In contrast, designing a study where SCR is the primary endpoint, is not an easy task because precision and statistical power are affected by the age distribution of a given population. Methods Two sample size calculators for SCR estimation are proposed. The first one consists of transforming the confidence interval for SP into the corresponding one for SCR given a known seroreversion rate (SRR). The second calculator extends the previous one to the most common situation where SRR is unknown. In this situation, data simulation was used together with linear regression in order to study the expected relationship between sample size and precision. Results The performance of the first sample size calculator was studied in terms of the coverage of the confidence intervals for SCR. The results pointed out to eventual problems of under or over coverage for sample sizes ≤250 in very low and high malaria transmission settings (SCR ≤ 0.0036 and SCR ≥ 0.29, respectively). The correct coverage was obtained for the remaining transmission intensities with sample sizes ≥ 50. Sample size determination was then carried out for cross-sectional surveys using realistic SCRs from past sero-epidemiological studies and typical age distributions from African and non-African populations. For SCR < 0.058, African studies require a larger sample size than their non-African counterparts in order to obtain the same precision. The opposite happens for the remaining transmission intensities. With respect to the second sample size calculator, simulation unravelled the likelihood of not having enough information to estimate SRR in low transmission settings (SCR ≤ 0.0108). In that case, the respective estimates tend to underestimate the true SCR. This problem is minimized by sample sizes of no less than 500 individuals. The sample sizes determined by this second method highlighted the prior expectation that, when SRR is not known, sample sizes are increased in relation to the situation of a known SRR. In contrast to the first sample size calculation, African studies would now require lesser individuals than their counterparts conducted elsewhere, irrespective of the transmission intensity. Conclusions Although the proposed sample size calculators can be instrumental to design future cross-sectional surveys, the choice of a particular sample size must be seen as a much broader exercise that involves weighting statistical precision with ethical issues, available human and economic resources, and possible time constraints. Moreover, if the sample size determination is carried out on varying transmission intensities, as done here, the respective sample sizes can also be used in studies comparing sites with different malaria transmission intensities. In conclusion, the proposed sample size calculators are a step towards the design of better sero-epidemiological studies. Their basic ideas show promise to be applied to the planning of alternative sampling schemes that may target or oversample specific age groups

Freedom from Infection: Confirming Interruption of Malaria Transmission.

: The global reductions in disease burden and the continued spread of drug and insecticide resistance make malaria elimination both viable and imperative, although this may be more easily achieved in some settings compared to others. Whilst the focus has been on optimal approaches to achieve elimination, less attention has been paid to how to measure the absence of malaria. Measuring the absence of transmission poses a specific challenge in that it involves proving a negative. The concept of freedom from infection, routinely used in veterinary epidemiology, can provide quantitative and reproducible estimates that, if infections were present above a predefined (low) threshold, they would be detected with a known uncertainty. Additionally, these methods are adaptable for both passively and actively collected data as well as combining information when multiple surveillance streams are available. Here we discuss the potential application of this approach to malaria.<br/

Dynamics of P. falciparum gametocytemia in symptomatic patients in an area of intense perennial transmission in Tanzania.

We investigated the dynamics of Plasmodium falciparum gametocytemia in symptomatic patients attending a local dispensary in the Kilombero district, Tanzania. Consenting individuals aged one and above, with varying asexual and sexual parasitemias were treated appropriately and asked to return weekly for 28 days. Gametocyte prevalence was highest on Day 7 of follow-up in all age groups (overall 30.5%). Multifactorial analysis showed that young age (chi2 = 18.4; P = 0.004), high asexual parasitemia on presentation (chi2 = 19.4; P = 0.0007) and gametocyte positivity on presentation (chi2 = 29.4; P = 0.001) were all significantly associated with the presence of gametocytes on Days 7 and 14 of follow-up. High presentation of asexual parasitemia alone was positively correlated with higher gametocyte densities on both days of follow-up (F4, 297 = 2.0; P = 0.049). Gametocyte incidence rates decreased significantly with age (chi2 = 7.6, P < 0.005). In summary, in this group of chloroquine-treated individuals, gametocyte prevalence and incidence rates decreased with age, while densities remained relatively constant

Dynamics of P. Falciparum Gametocytemia in Symptomatic Patients in an Area of Intense Perennial Transmission in Tanzania.

We investigated the dynamics of Plasmodium falciparum gametocytemia in symptomatic patients attending a local dispensary in the Kilombero district, Tanzania. Consenting individuals aged one and above, with varying asexual and sexual parasitemias were treated appropriately and asked to return weekly for 28 days. Gametocyte prevalence was highest on Day 7 of follow-up in all age groups (overall 30.5%). Multifactorial analysis showed that young age (chi2 = 18.4; P = 0.004), high asexual parasitemia on presentation (chi2 = 19.4; P = 0.0007) and gametocyte positivity on presentation (chi2 = 29.4; P = 0.001) were all significantly associated with the presence of gametocytes on Days 7 and 14 of follow-up. High presentation of asexual parasitemia alone was positively correlated with higher gametocyte densities on both days of follow-up (F4, 297 = 2.0; P = 0.049). Gametocyte incidence rates decreased significantly with age (chi2 = 7.6, P < 0.005). In summary, in this group of chloroquine-treated individuals, gametocyte prevalence and incidence rates decreased with age, while densities remained relatively constant

Low-dose primaquine for falciparum malaria

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Artesunate reduces but does not prevent posttreatment transmission of Plasmodium falciparum to Anopheles gambiae.

Combination therapy that includes artemisinin derivatives cures most falciparum malaria infections. Lowering transmission by reducing gametocyte infectivity would be an additional benefit. To examine the effect of such therapy on transmission, Gambian children with Plasmodium falciparum malaria were treated with standard regimens of chloroquine or pyrimethamine-sulfadoxine alone or in combination with 1 or 3 doses of artesunate. The infectivity to mosquitoes of gametocytes in peripheral blood was determined 4 or 7 days after treatment. Infection of mosquitoes was observed in all treatment groups and was positively associated with gametocyte density. The probability of transmission was lowest in those who received pyrimethamine-sulfadoxine and 3 doses of artesunate, and it was 8-fold higher in the group that received pyrimethamine-sulfadoxine alone. Artesunate reduced posttreatment infectivity dramatically but did not abolish it completely. The study raises questions about any policy to use pyrimethamine-sulfadoxine alone as the first-line treatment for malaria

The fine-scale genetic structure of the malaria vectors Anopheles funestus and Anopheles gambiae (Diptera: Culicidae) in the north-eastern part of Tanzania

AbstractUnderstanding the impact of altitude and ecological heterogeneity at a fine scale on the populations of malaria vectors is essential to better understand and anticipate eventual epidemiological changes. It could help to evaluate the spread of alleles conferring resistance to insecticides and also determine any increased entomological risk of transmission in highlands due to global warming. We used microsatellite markers to measure the effect of altitude and distance on the population genetic structure ofAnopheles funestusandAnopheles gambiae s.s. in the Muheza area in the north-eastern part of Tanzania (seven loci for each species). Our analysis reveals strong gene flow between the different populations ofAn. funestusfrom lowland and highland areas, as well as between populations ofAn. gambiaesampled in the lowland area. These results highlight forAn. funestusthe absence of a significant spatial subpopulation structuring at small-scale, despite a steep ecological and altitudinal cline. Our findings are important in the understanding of the possible spread of alleles conferring insecticide resistance through mosquito populations. Such information is essential for vector control programmes to avoid the rapid spread and fixation of resistance in mosquito populations.</jats:p

Validation of three geolocation strategies for health-facility attendees for research and public health surveillance in a rural setting in western Kenya.

Understanding the spatial distribution of disease is critical for effective disease control. Where formal address networks do not exist, tracking spatial patterns of clinical disease is difficult. Geolocation strategies were tested at rural health facilities in western Kenya. Methods included geocoding residence by head of compound, participatory mapping and recording the self-reported nearest landmark. Geocoding was able to locate 72·9% [95% confidence interval (CI) 67·7-77·6] of individuals to within 250 m of the true compound location. The participatory mapping exercise was able to correctly locate 82·0% of compounds (95% CI 78·9-84·8) to a 2 × 2·5 km area with a 500 m buffer. The self-reported nearest landmark was able to locate 78·1% (95% CI 73·8-82·1) of compounds to the correct catchment area. These strategies tested provide options for quickly obtaining spatial information on individuals presenting at health facilities

Reducing Plasmodium falciparum malaria transmission in Africa: a model-based evaluation of intervention strategies.

BACKGROUND: Over the past decade malaria intervention coverage has been scaled up across Africa. However, it remains unclear what overall reduction in transmission is achievable using currently available tools. METHODS AND FINDINGS: We developed an individual-based simulation model for Plasmodium falciparum transmission in an African context incorporating the three major vector species (Anopheles gambiae s.s., An. arabiensis, and An. funestus) with parameters obtained by fitting to parasite prevalence data from 34 transmission settings across Africa. We incorporated the effect of the switch to artemisinin-combination therapy (ACT) and increasing coverage of long-lasting insecticide treated nets (LLINs) from the year 2000 onwards. We then explored the impact on transmission of continued roll-out of LLINs, additional rounds of indoor residual spraying (IRS), mass screening and treatment (MSAT), and a future RTS,S/AS01 vaccine in six representative settings with varying transmission intensity (as summarized by the annual entomological inoculation rate, EIR: 1 setting with low, 3 with moderate, and 2 with high EIRs), vector-species combinations, and patterns of seasonality. In all settings we considered a realistic target of 80% coverage of interventions. In the low-transmission setting (EIR approximately 3 ibppy [infectious bites per person per year]), LLINs have the potential to reduce malaria transmission to low levels (90%) or novel tools and/or substantial social improvements will be required, although considerable reductions in prevalence can be achieved with existing tools and realistic coverage levels. CONCLUSIONS: Interventions using current tools can result in major reductions in P. falciparum malaria transmission and the associated disease burden in Africa. Reduction to the 1% parasite prevalence threshold is possible in low- to moderate-transmission settings when vectors are primarily endophilic (indoor-resting), provided a comprehensive and sustained intervention program is achieved through roll-out of interventions. In high-transmission settings and those in which vectors are mainly exophilic (outdoor-resting), additional new tools that target exophagic (outdoor-biting), exophilic, and partly zoophagic mosquitoes will be required

Documentation of a fully integrated epidemiological-demographic-macroeconomic model of Malaria: The case of Ghana

We develop a novel and fully integrated epidemiological-demographic-macroeconomic EDM-malaria simulation model framework for modelling of P. falciparum malaria transmission in Ghana. Our model framework represents a milestone, as the first fully integrated EDM model framework for any type of infectious disease. The complex specification and integration of regional epidemiological-demographic models within a malaria-focussed macroeconomic Computable General Equilibrium model is fully described and documented, and ideas are outlined for future applications to investigate the interplay between macroeconomic and health disease burdens, to measure the health and economic impacts of economic growth and malaria interventions, and to study the importance (or lack thereof) of the general omission of proper epidemiological underpinnings and integration of economic incentive feedback effects in the existing literature on macroeconomic assessment of infectious disease