The Plasmodium falciparum-Specific Human Memory B Cell Compartment Expands Gradually with Repeated Malaria Infections

Immunity to Plasmodium falciparum (Pf) malaria is only acquired after years of repeated infections and wanes rapidly without ongoing parasite exposure. Antibodies are central to malaria immunity, yet little is known about the B-cell biology that underlies the inefficient acquisition of Pf-specific humoral immunity. This year-long prospective study in Mali of 185 individuals aged 2 to 25 years shows that Pf-specific memory B-cells and antibodies are acquired gradually in a stepwise fashion over years of repeated Pf exposure. Both Pf-specific memory B cells and antibody titers increased after acute malaria and then, after six months of decreased Pf exposure, contracted to a point slightly higher than pre-infection levels. This inefficient, stepwise expansion of both the Pf-specific memory B-cell and long-lived antibody compartments depends on Pf exposure rather than age, based on the comparator response to tetanus vaccination that was efficient and stable. These observations lend new insights into the cellular basis of the delayed acquisition of malaria immunity

Plasmodium falciparum transcription in different clinical presentations of malaria associates with circulation time of infected erythrocytes

Following Plasmodium falciparum infection, individuals can remain asymptomatic, present with mild fever in uncomplicated malaria cases, or show one or more severe malaria symptoms. Several studies have investigated associations between parasite transcription and clinical severity, but no broad conclusions have yet been drawn. Here, we apply a series of bioinformatic approaches based on P. falciparum’s tightly regulated transcriptional pattern during its ~48-hour intraerythrocytic developmental cycle (IDC) to publicly available transcriptomes of parasites obtained from malaria cases of differing clinical severity across multiple studies. Our analysis shows that within each IDC, the circulation time of infected erythrocytes without sequestering to endothelial cells decreases with increasing parasitaemia or disease severity. Accordingly, we find that the size of circulating infected erythrocytes is inversely related to parasite density and disease severity. We propose that enhanced dhesiveness of infected erythrocytes leads to a rapid increase in parasite burden, promoting higher parasitaemia and increased disease severity

Seasonality and Prevalence of Leishmania major Infection in Phlebotomus duboscqi Neveu-Lemaire from Two Neighboring Villages in Central Mali

Phlebotomus duboscqi is the principle vector of Leishmania major, the causative agent of cutaneous leishmaniasis (CL), in West Africa and is the suspected vector in Mali. Although found throughout the country the seasonality and infection prevalence of P. duboscqi has not been established in Mali. We conducted a three year study in two neighboring villages, Kemena and Sougoula, in Central Mali, an area with a leishmanin skin test positivity of up to 45%. During the first year, we evaluated the overall diversity of sand flies. Of 18,595 flies collected, 12,952 (69%) belonged to 12 species of Sergentomyia and 5,643 (31%) to two species of the genus Phlebotomus, P. duboscqi and P. rodhaini. Of those, P. duboscqi was the most abundant, representing 99% of the collected Phlebotomus species. P. duboscqi was the primary sand fly collected inside dwellings, mostly by resting site collection. The seasonality and infection prevalence of P. duboscqi was monitored over two consecutive years. P. dubsocqi were collected throughout the year. Using a quasi-Poisson model we observed a significant annual (year 1 to year 2), seasonal (monthly) and village effect (Kemena versus Sougoula) on the number of collected P. duboscqi. The significant seasonal effect of the quasi-Poisson model reflects two seasonal collection peaks in May-July and October-November. The infection status of pooled P. duboscqi females was determined by PCR. The infection prevalence of pooled females, estimated using the maximum likelihood estimate of prevalence, was 2.7% in Kemena and Sougoula. Based on the PCR product size, L. major was identified as the only species found in flies from the two villages. This was confirmed by sequence alignment of a subset of PCR products from infected flies to known Leishmania species, incriminating P. duboscqi as the vector of CL in Mali

Forecasting Non-Stationary Diarrhea, Acute Respiratory Infection, and Malaria Time-Series in Niono, Mali

BACKGROUND: Much of the developing world, particularly sub-Saharan Africa, exhibits high levels of morbidity and mortality associated with diarrhea, acute respiratory infection, and malaria. With the increasing awareness that the aforementioned infectious diseases impose an enormous burden on developing countries, public health programs therein could benefit from parsimonious general-purpose forecasting methods to enhance infectious disease intervention. Unfortunately, these disease time-series often i) suffer from non-stationarity; ii) exhibit large inter-annual plus seasonal fluctuations; and, iii) require disease-specific tailoring of forecasting methods. METHODOLOGY/PRINCIPAL FINDINGS: In this longitudinal retrospective (01/1996-06/2004) investigation, diarrhea, acute respiratory infection of the lower tract, and malaria consultation time-series are fitted with a general-purpose econometric method, namely the multiplicative Holt-Winters, to produce contemporaneous on-line forecasts for the district of Niono, Mali. This method accommodates seasonal, as well as inter-annual, fluctuations and produces reasonably accurate median 2- and 3-month horizon forecasts for these non-stationary time-series, i.e., 92% of the 24 time-series forecasts generated (2 forecast horizons, 3 diseases, and 4 age categories = 24 time-series forecasts) have mean absolute percentage errors circa 25%. CONCLUSIONS/SIGNIFICANCE: The multiplicative Holt-Winters forecasting method: i) performs well across diseases with dramatically distinct transmission modes and hence it is a strong general-purpose forecasting method candidate for non-stationary epidemiological time-series; ii) obliquely captures prior non-linear interactions between climate and the aforementioned disease dynamics thus, obviating the need for more complex disease-specific climate-based parametric forecasting methods in the district of Niono; furthermore, iii) readily decomposes time-series into seasonal components thereby potentially assisting with programming of public health interventions, as well as monitoring of disease dynamics modification. Therefore, these forecasts could improve infectious diseases management in the district of Niono, Mali, and elsewhere in the Sahel

A feasibility study for the preparation of educational administrators in the Republic of Mali.

Schools seek to educate people in order for them to be functional or productive agents in the society. In Mali, schools have experienced a rapid development in a post-colonial environment. The needs have outdistanced the resources and commitment necessary for orderly and progressive growth. Developments in recent years have also generated increased demands on educational administrators, making their jobs more challenging than ever. Such administrators are central to the improvement of the schools. At present there is no process of systematically training these people. This study analyzes the need for, and the possibility of, implementing an educational administration preparation program for school administrators in the Republic of Mali. It then proposes one way of organizing this educational administration preparation program. The diagnosis of educational administrative practice in Mali revealed a serious need for the preparation of educational administrators. To undertake the diagnosis, the current study sought information from national documents, from incumbent educational administrators, and also from a random sample of principals, teachers, students, parents, and educational administration officials. Having diagnosed the problems, the study then develops a proposal for remedying the problems in the form of educational administration preparation program

Disease consultation frequencies for the district of Niono.

<p>Disease consultation frequencies for the district of Niono are expressed as percentages (%) from the total number of recorded consultations during the investigational period (01/1996–06/2004). Diarrhea, acute respiratory infection (ARI) of the lower tract, and malaria account for 59.2% of all consultations (333 990) that were recorded in the district of Niono <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001181#pone.0001181-Division1" target="_blank">[39]</a> during this period. For comparison, the disease frequencies for the district of Gao (2005) are also displayed <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001181#pone.0001181-Division2" target="_blank">[41]</a> in the last column. This table confirms that targeting diarrhea, ARI, and malaria is imperative to reduce morbidity, and presumably mortality, in the district of Niono, Mali.</p

Forecasts for acute respiratory infection (ARI) consultation rate time-series.

<p>Observed ARI consultation rate time-series are depicted as black lines while red and blue traces correspond to contemporaneous 2- and 3-month horizon forecasts, respectively; their prediction interval bounds are symbolized by dots of the same colors. Forecasts and prediction interval bounds are calculated with a bootstrap-coupled seasonal multiplicative Holt-Winters method (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001181#s4" target="_blank"><i>Methods</i></a>). In each panel, the abscissa spans 102 months (01/1996–06/2004) while the ordinate represents the number of newly diagnosed cases <i>per</i> 1000 age category-specific individuals. Panel A: 0–11 months; Panel B: 1–4 years; Panel C: 5–15 years; and, Panel D: >15 years. Forecasts deteriorate slightly towards older age categories owing to seasonality attenuation. Of note, age category-specific 2- and 3-month horizon ARI consultation rate forecasts roughly overlap because of slowly shifting level and negligible trend time-series components. Consequently, 2- and 3-month horizon 95% prediction interval bounds also overlap.</p

Demographic and consultation record descriptions.

<p>The projected number of individuals (2004) served by each community health center (CSCOM) service area within the district of Niono, Mali, is tabulated under the <i>Population</i> heading. Potential records are listed under <i>Time-series period</i>. Unavailable CSCOM service area records appear under <i>Missing dates</i>—the number of missing monthly records for each year is listed in parenthesis otherwise records for the whole year are missing. These are totaled under <i>Missing months</i> and expressed as percentages from the total number of possible monthly records (across all CSCOM service areas) under the <i>% missing</i> heading. Monthly consultation records from each CSCOM service area are adjusted with the annual national population growth rate before missing records are interpolated by CSCOM-specific monthly median values. The total projected population (2004) for the district of Niono is 278 741 individuals, growing 3.2% annually according to regional <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001181#pone.0001181-Division1" target="_blank">[39]</a> and national <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001181#pone.0001181-USAID1" target="_blank">[40]</a> estimates. In the context of consultation rates, years with more than 6 missing monthly records are excluded from median and inter-quartile-range annual consultation rate calculations. Additionally, inter-quartile-range calculations require records from at least 3 eligible years. In the time-series context, however, the projected district population (2004) reduces from 278 741 to 208 743 individuals upon record exclusion from Fassoum, Nara, and Niono CSCOM service areas—which do not span the entire investigational period and possess excessive missing monthly records. Values that are reported in parenthesis under the headings of <i>Population</i> (2004), <i>time-series period</i>, <i>Missing months</i>, and <i>% missing</i> reflect record exclusion from Fassoum, Nara, and Niono CSCOM service areas. After record exclusion, the remaining 14 CSCOM service areas contribute 1428 possible monthly records to the amalgamated time-series, i.e., 14 records <i>per</i> month. Of note, the Niono CSCOM service area, which includes the district center and immediate periphery, is one of the 17 CSCOM service areas within the district of Niono, Mali.</p

Forecasts for malaria consultation rate time-series.

<p>Observed malaria consultation rate time-series are depicted as black lines while red and blue traces correspond to contemporaneous 2- and 3-month horizon forecasts, respectively; their prediction interval bounds are symbolized by dots of the same colors. Forecasts and prediction interval bounds are calculated with a bootstrap-coupled seasonal multiplicative Holt-Winters method (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001181#s4" target="_blank"><i>Methods</i></a>). The abscissa spans 102 months (01/1996–06/2004) while the ordinate represents the number of newly diagnosed cases <i>per</i> 1000 age category-specific individuals. Panel A: 0–11 months; Panel B: 1–4 years; Panel C: 5–15 years; and, Panel D: >15 years. Forecasts ameliorate towards older age categories owing to seasonality accentuation. Visual inspection suggests a resemblance between ARI (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0001181#pone-0001181-g004" target="_blank">Fig. 4</a>) and malaria time-series, as well as forecasts, for the youngest age category (Panel A: 0–11 months), which might reflect misdiagnosis and or co-morbidity between these two diseases. Clinical diagnosis among infants suffers from two major limitations. Infants are <i>i</i>) immunologically complex and <i>ii</i>) unable to effectively communicate symptoms. Of note, age category-specific 2- and 3-month horizon malaria consultation rate forecasts roughly overlap because of slowly shifting level and negligible trend time-series components. Consequently, 2- and 3-month horizon 95% prediction interval bounds also overlap.</p